Paper Reading #27: Sensing cognitive multitasking for a brain-based adaptive user interface

References

Erin Treacy Solovey, Francine Lalooses, Krysta Chauncey, Douglas Weaver, Margarita Parasi, Matthias Scheutz, Angelo Sassaroli, Sergio Fantini, Paul Schermerhorn, Audrey Girouard, Robert J.K. Jacob.  "Gesture avatar: a technique for operating mobile user interfaces using gestures". UIST '11 Proceedings of the 23rd annual ACM symposium on User interface software and technology.  ACM New York, NY, USA ©2011.

 Author Bios

This research paper involved all people from Tufts University. Everyone on the list is either a post-graduate student, a professor, or a researcher at or for the University.

Summary 

• Hypothesis - The hypothesis is that an fNIRS tool will be as effective in capturing the tasking of a human mind as an fMRI machine. The researcher also hypothesized that a system using this tool can be created that will aid users in their tasks.
• Method - The experiment involved participants interacting with a robot simulation, in which they sorted rocks on Mars. Based on the pattern of rock classifications, they then divide tasking into three groups: delay, dual-tasking, and branching. They also tested whether the fNIRS tool would truly be as effected as the fMRI. They asked users to do varying tasked and analyzed how often the fNIRS tool correctly classified their tasking state.
• Results - The fNIRS was able to correctly classify some tasking states, but was not very accurate. The researchers noted that there were certain modifications that could be made to improve this statistic. They also created a system based off of this data in order to test the ability of a system to help users in multitasking.
• Content - The researchers compared the fNIRS machine to an fMRI machine, and noted that the fNIRS was not as accurate or as powerful as the fMRI, but that in a real-world application it is much more feasible. They then created a system to use the fNIRS to help users in their multitasking. The system showed some good results, hinting that it may be a good direction to follow.

 Discussion

This paper held my interest well. I (attempt to) multitask all the time, and frequently am bogged down by the time it takes to switch between the proper state of mind for each task. Going from phone to programming to email and back to programming takes much longer than it could, because I often do not wait to get to a stopping point before switching tasks. As I just did. And I lost my train of thought...well I suppose this blog's done.

Paper Reading #26: Embodiment in Brain-Computer Interaction

Paper Reading #24: Gesture avatar: a technique for operating mobile user interfaces using gestures

References

Kenton O'Hara, Abigail Sellen, Richard Harper.  "Embodiment in Brain-Computer Interaction". UIST '11 Proceedings of the 23rd annual ACM symposium on User interface software and technology.  ACM New York, NY, USA ©2011.

 Author Bios

Kenton O'Hara is a Senior Researcher at Microsoft Research.

Abigail Sellen is a Principal Researcher at Microsoft Research. She received her Ph. D. from the University of California San Diego.

Richard Harper is a Principal Researcher at Microsoft Research. He received his Ph. D. from Manchester.

Summary 

• Hypothesis -The researchers hypothesized that in brain-computer interaction, the whole body and social interactions are equally important for study.
• Method - The study used a game called MindFlex. Three groups were given the game to take home and video themselves playing it. They were encouraged to bring in random people such as outside family and friends to play as well. They were told to choose where and when to play, allowing for a natural environment.
• Results - The analysis showed many different things that was not necessary for impacting the game. For example, body position played a large role in how users interacted with the game, although it had no direct effect. Another is that users would frequently use imaging, such as imagining or telling the ball to go up when all they needed to do was concentrate more.
• Content - The researchers analyzed the interactions between players and between player and game in order to better understand how brain-computer interaction works. They told different groups to play the game while acting naturally, in order to get a representation that was as little skewed as possible. They observed many common patterns between players.

 Discussion

I thought that the game itself was interesting, but found that the paper didn't seem to hold much application. It more or less was saying that we need to study brain-computer interaction more in order to expand the field, which seems to me pretty obvious. However, the paper was well done and I enjoyed the experiment itself. Some of the observations they found were surprising to me. I would like to play that game, as I'm not sure I would do very well; unlike some people, I can't ever stop thinking and can't "turn my brain off".

Paper Reading #25: TwitInfo: Aggregating and Visualizing Microblogs For Event Exploration

References

Adam Marcus, Michael S. Bernstein, Osama Badar, David R. Karger, Samuel Madden, Robert C. Miller.  "TwitInfo: Aggregating and Visualizing Microblogs For Event Exploration". UIST '11 Proceedings of the 23rd annual ACM symposium on User interface software and technology.  ACM New York, NY, USA ©2011.

 Author Bios

Adam Marcus is a graduate student at MIT. He received his bachelor's from Rensselaer Plytechnic Institute.

Michael S. Bernstein research interests lie in social computing and crowdsourcing.

Osama Badar is a graduate student at MIT.

David R. Karger used to work for Google, and is now a part of the AI lab at MIT.

Samuel Madden is an associate professor at MIT. He has worked on systems for mTurk.

Robert C. Miller is an associate professor at MIT. He currently leads the User Interface Design Group.

Summary 

• Hypothesis - A study of massive amounts of microblogs can provide accurate feedback on major events in real time, in this case Twitter.
• Method -The researchers developed TwitInfo, which analyzes all posts with specific tags. These tags are set for an event, such as a World Cup Game. They developed a user interface that was intuitive for users and analyzed events in real time. They then evaluated the usefulness by letting average users test it, as well as a major journalist.
• Results - The results were favorable. The evaluation showed that TwitInfo was accurately able to predict when events occurred. It was also able to analyze on a basic level people's reactions to that event. For example, during a World Cup game, it was able to localize where people were generally happy or generally unhappy towards certain events, such as goals. The journalist maintained that this knowledge was too shallow to rely on alone, but that it was a useful tool to gain a basic understanding at a higher level.
• Content - The paper presented a tool for analyzing Twitter information to gain accurate data on world events. It was able to do so rather successfully, and users generally gave positive feedback. The limitations on this system was that it was not able to show all of the major events, such as a yellow card in the World Cup game, and that the information gathered is too shallow to use as a sole source of data.

 Discussion

This tool impressed me. I rather liked how it was developed, and it was pretty fun to look at the UI (while it was still up and working). I liked how it was able to analyze the massive amounts of data in real time. The sentiment calculation left something to be desired, but such is our current technology. I particularly liked the World Cup game, as it was interesting to see which events were portrayed accurately and what went undetected.

Paper Reading #24: Gesture avatar: a technique for operating mobile user interfaces using gestures

References

Hao Lu, Yang Li.  "Gesture avatar: a technique for operating mobile user interfaces using gestures". UIST '11 Proceedings of the 23rd annual ACM symposium on User interface software and technology.  ACM New York, NY, USA ©2011.

 Author Bios

Yang Li received his Ph.D. from the Chinese Academy of Sciences and conducted postdoctoral research at the University of California at Berkeley. Li helped found the Design Use Build (DUB) community while a professor at the University of Washington. He is now a Senior Research Scientist at Google.

Hao Lu is a graduate student at the University of Washington. He is a member of the DUB group.

Summary 

• Hypothesis - The researchers had three hypotheses:
• Gesture Avatar would be slower than Shift on large targets, but faster on small ones.
• Gesture Avatar will be less error-prone than Shift.
• The error rate for Gesture Avatar will not be affected as much by walking as Shift's.
• Method - The participants were to test both systems. Half of them learned Gesture Avatar first, half Shift. The researchers then measured the time from gesture to selection with many variables, such as walking or sitting, number of repeated letters, and the size of the targets. They then compared the results between Gesture Avatar and Shift.
• Results - The results confirmed hypothesis 1: Shift was much faster on large targets, but much slower on small ones. The error rate for Gesture Avatar remained mostly constant, while Shift's went up as target size became smaller. They also confirmed the third hypothesis; Gesture Avatar remained constant between sitting and walking, while Shaft's performance decreased significantly. Only one participant in the study preferred Shift over Gesture Avatar.
• Content -The paper presented the implementation for Gesture Avatar, an API geared towards minimizing errors due to touch-screen based selection. They suggested minor adjustments and modifications to their system that are possible and may be desirable. They developed their product and tested it against Shift to test its strengths and weaknesses. Their results matched their hypotheses and Gesture Avatar had an overall good reception.

 Discussion

 I appreciated the clarity of this paper, and also how relevant its application was to the the general populace. I personally have some troubles (having fat fingers) while selecting small text in a web browser. I have not used Gesture Avatar yet but may pick it up, as it seems others have had good results. I don't particularly like letter-based gestures as a whole, as they can fail at recognizing letters correctly. However, due to the relative simplicity of this one's use, the gesture errors may be minimized more because does not require as much input.

Paper Reading #22: Mid-air Pan-and-Zoom on Wall-sized Displays

References

Mathieu Nancel, Julie Wagner, Emmanuel Pietriga, Olivier Chapuis, and Wendy Mackay.  "Mid-air pan-and-zoom on wall-sized displays". UIST '11 Proceedings of the 23rd annual ACM symposium on User interface software and technology.  ACM New York, NY, USA ©2011.

 Author Bios

Mathieu Nancel is a Ph.D. student in HCI at the University Paris-Sud XI.

Julie Wagner is a Ph.D. student at the InSitu lab in Paris.

Emmanuel Pietriga is the interim leader of INRIA team in Situ where he is a full-time reasearch scientist.

Oliver Chapuis is a research scientiest at LRI. He is also a member of the InSitu research team.

Wendy Mackay is a research director with INRIA Saclay in France. She is in charge of the research group InSitu.

Summary 

• Hypothesis - The researchers hypothesized that they could improve interaction with wall-sized displays by studying several factors of gesture interactions. They made an individual hypothesis for each factor:
•  Two-handed gestures are more accurate and easier to use.
• Two-handed gestures are faster than one-handed.
•  Users will prefer clutch-free gestures.
• Linear gestures would be best mapped to zoom but should eventually be slower due to aforementioned clutching.
• Gestures utilizing fingers instead of larger muscle groups will be faster.
• One-dimensional path gestures should be faster when using lesser haptic feedback.
• Three-dimensional gestures will be more tiring.
• Method - Their study involved 12 participants. Each participant was asked to use all patterns of interaction. Each participant completed these patterns in a number of sessions, preventing inaccurate data caused by exhaustion and memory loss.
• Results - The results found supported the second hypothesis, as well as the fifth and sixth. The fourth hypothesis was refuted; linear gestures actually ended up being faster than circular gestures. Hypothesis seven was also found to be true. The results for the other hypotheses were inconclusive.
• Content - This paper discusses the best ways a user might interact with a screen too large to interact with directly. They form several hypotheses on how well certain gestures would work, and perform a study based around their hypotheses. They then conducted an experiment to emphasize their key points.

 Discussion

This paper was very interesting. I though their methods may have been a little off, but their results were for the most part expected. I can't say whether or not they thoroughly proved their points, but the paper was well done. Technology like this makes me excited every time I read about it; we keep getting closer to virtual reality rooms and smooth motion gestures for all interactions. I can't wait for the day that I have a display on all of my walls and can change anything I want with a word and a hand gesture.

Paper Reading #21: Human model evaluation in interactive supervised learning

References

Rebecca Fiebrink, Perry R. Cook, and Dan Trueman.  "Reflexivity in digital anthropology". UIST '11 Proceedings of the 23rd annual ACM symposium on User interface software and technology.  ACM New York, NY, USA ©2011.

 Author Bios

Rebecca Fiebrink is an assistant professor in Computer Science and affiliated faculty in Music. Until recently she was a postdoc at the University of Washington.

Perry Cook earned his PhD from Stanford University.  His research interests lie in Physics-based sound synthesis models.

Dan Trueman is a professor at Princeton University.  In the last 12 years he has published 6 papers through the ACM. He is also a musician, primarily with the fiddle and the laptop.

Summary 

• Hypothesis - The researchers hypothesized that Interactive Machine Learning (IML) would be a useful tool to improve the current generic machine learning processes currently used.
• Method -The researchers first developed a system of IML to help with music composition, called Wekinator. They then conducted three studies. The first study included several PhD students aimed towards improving the system itself. They used the software while composing their own music, and met regularly to discuss their experiences and suggest improvements for the software. The second study involved undergraduates. They were told to use the software in an assignment specifically geared towards supervised learning in interactive music performance systems. The third and final study had a professional cellist use the system to create a gesture recognition system. The gestures were to provide correct musical notation, such as staccato.
• Results -  Although some results were expected, they also ran into a few things they had not. For one, users tended to overcompensate; that is, they provided more than enough information to make sure the system got it right. Also, the system's performance sometimes surprised users, encouraging them to expand their ideas of the desired goal.
  
• Content - The researchers observed as users interacted with the machine learning software. They found that while users liked the cross-validation, most of them preferred direct validation. The IML was determined to be useful because of its ability to continuously improve the effectiveness of the learning model itself.

 Discussion

This paper was very well done. The experiments were well thought out, carried out, and explained. The proved their hypothesis and were successful in explaining why. Using three independent studies, they were able to compile a large amount of data to use. I think that these results will be very useful, not just in the application they chose but in a widespread realm of problems. 

Paper Reading #20:The aligned rank transform for nonparametric factorial analyses using only anova procedures

References

Jacob O. Wobbrock, Leah Findlater, Darren Gergle, and James J. Higgins.  "Reflexivity in digital anthropology". UIST '11 Proceedings of the 23rd annual ACM symposium on User interface software and technology.  ACM New York, NY, USA ©2011.

 Author Bios

Jacob Wobbrock is an associate professor in the Information School at the University of Washington.  He directs the AIM Research Group which is part of the DUB Group.

Leah Findlater is currently a professor at the University of Washington.

Darren Gergle is an associate professor at the Northwestern University School of Communication.

James Higgins is a professor in the Department of Statistics at Kansas State Unversity. 

Summary 

• Hypothesis - The researchers hypothesized that modifying the Aligned Rank Transform to support an arbitrary number of factors would be useful for researchers in analyzing data.
• Method - The researchers developed the method for the expanded ART and then created a desktop tool (ARTool) and a Java-based verson (ARTWeb). After creating these tools the researchers analyzed three sets of previously published data. This analysis allowed them to show the effectiveness and usability of their software.
• Results - The results were positive. Reexamining old studies showed data that had not shown up before. For one of them, data was found that was unexaminable by a Friedman test. The second case showed how the new system can free analysts from assuming distributions of ANOVA. The last was run using the nonparametric ART method, new information was revealed.
• Content - The authors presented their Aligned Rank Transform (ART) tool, which is useful for nonparametric analysis of factorial experiments. They discuss the process in detail, and show three examples of how it is useful and where it is applicable. It is shown that this tool can show some relationships between variables that cannot be seen with other analyses.

 Discussion

Honestly, this paper went way over my head. It did seem obvious to me, however, that the authors were able to effectively support their hypothesis and were able to create a very useful tool for analysts. The amount of information analysts gets out of data greatly affects their ability to extrapolate. I thought their examples were well chosen and explained well (even on a broad spectrum) how the ART system can produce more specific and more accurate results.

Paper Reading #19: Reflexivity in Digital Antrhopology

References

Jennifer A. Rode.  "Reflexivity in digital anthropology". UIST '11 Proceedings of the 23rd annual ACM symposium on User interface software and technology.  ACM New York, NY, USA ©2011.

 Author Bios

Jennifer Rode is an assistant professor at Drexel's School of Information. Rode has produced several interface design projects. She received her PhD from the University of California, Irvine.

Summary 

• Hypothesis - Rode hypothesized that some methods of digital anthropology can be utilized by researchers while conducting field studies.
• Method - This paper did not contain any user studies, and thus no methods were presented.
• Results -  The author spent most of this paper describing different methods of ethnographic study, namely Positivist and Reflexivity, where the definitions were from previous research. She then goes on to argue why many of these unused methods could be beneficial in digital research.
• Content -The author discussed the various forms of ethnography, and how reflexivity can help in the design process for HCI.

 Discussion

This paper seemed to me to be a lot of explanation for not a lot of concept. It wasn't very concise and the author tended to ramble a bit. It was a bit hard to get through, but had a good overall concept: don't ignore the users you're developing for. However, she had no proof to prove her point, and she had little of her own ideas in the first place. Her main point was that bringing together certain already established methodologies can help aid HCI.

Paper Reading #18: Biofeedback game design: using direct and indirect physiological control to enhance game interaction

References

Lennart Erik Nacke, Michael Kalyn, Calvin Lough, and Regan Lee Mandryk.  "Biofeedback game design: using direct and indirect physiological control to enhance game interaction". UIST '10 Proceedings of the 23rd annual ACM symposium on User interface software and technology.  ACM New York, NY, USA ©2010. 

 

Author Bios

Lennart Erik Nacke is an assistant professor for HCI and Game Science at University of Ontario Institute of Technology.

Michael Kalyn is currently a graduate student in Computer Engineering at the University of Saskatchewan. 

Calvin Lough is a student at the University of Saskatchewan

Regan Lee Mandryk is an associate professor at the University of Saskatchewan.

Summary 

• Hypothesis -They hypothesized that they can increase the enjoyment of video games by using physiological input to change the dynamics of the game.
• Method - The study consisted of 3 versions; the first was a control, where physiological input was not included. The second two used physiological input to augment a game controller for a  shooter game. After playing each version, the players were asked to fill out a questionnaire about their experiences.
• Results - The participants preferred when physiological input was mapped to more natural inputs, like flexing muscles to get more power out of something (jumping, for instance). They enjoyed the increased level of involvement, but they also expressed concern that it made gameplay more complicated. They also commented that it was a novel idea and that some of the sensors had a learning curve; however, once the learning curve was passed, it was on the whole a more rewarding experience.
• Content -The authors of this paper developed a simplistic shooter game that integrated physiological input with controllers. It explored the learning of new methods of controlling a game, and how the players were able to use them effectively. They concluded that physiological sensors can increase the enjoyment of video games. The indirect controls were shown to not be as enjoyable, as they did not present instant feedback.

 Discussion

This is the direction I've been expecting gaming to go for a long time. They already have certain aspects of physiological feedback in games, such as using music to increase a person's anxiety or excitement levels; it was only a matter of time before they started using physiological input to change the way a character moves or the way something can be used. In particular, breathing too hard in a stealthy game could cause enemies to become aware of you more easily; being more relaxed while sniping could decrease reticle movement, and so on. I'm ready for this type of thing to be implemented on a wide scale.

Paper Reading #17: Privacy Risks Emerging from the Adoption of InnocuousWearable Sensors in the Mobile Environment

References

Andrew Raij, Animikh Ghosh, Santosh Kumar, and Mani Srivastava.  "Privacy Risks Emerging from the Adoption of InnocuousWearable Sensors in the Mobile Environment". UIST '10 Proceedings of the 23rd annual ACM symposium on User interface software and technology.  ACM New York, NY, USA ©2010.

 Author Bios

Andrew B Raij is a Post-Doc fellow with the University of Memphis.

Animikh Ghosh spent time as a researcher at the University of Memphis.

Santosh Kumar is an associate professor at the University of Memphis.

Mani Bhushan Srivastava is a well known researcher from AT&T Bell Laboratories. He is currently a professor at UCLA.

Summary 

• Hypothesis -User concerns over privacy in terms of mobile devices due to the higher amount of personal devices that hold personal information.
• Method -The researchers divided 66 participants into two groups. One group was monitored for basic information for a week, while the other (the control group) was not monitored at all. Both groups filled out a survey at the beginning of the study to indicate their feelings on potentially private information in the next week. After the week was over, both groups again took a similar survey. Before the second survey, however, the monitored group was given the data collected on them and the conclusions drawn from that data.
• Results - The results from the second survey definitely indicated that those with a personal stake in the data expressed higher concerns about privacy than those without. The concern of those being monitored also showed increased concerns after the week. The researchers also found that the group of people the information would be given to changed the level of concern. Concern also increased when a schedule of behaviours or a timeline was created. The two main areas of concern were dealing with stress and conversations. Some were concerned that the wrong conclusions would be drawn because they wouldn't have the whole picture.
• Content - This paper discussed the growing public concern about privacy risks in the information age. The results from its study show that when the stakes are personal, the level of concern rises. The researchers proposed removing as much information from transmissions as possible.

 Discussion

This paper didn't register as a big deal for me. I purposefully keep things I want private off my cell phone and Facebook. I don't post things I don't want random people to see, for it's going to be seen, and I know that. If I have private information on my computer(s), I ensure that it has varying levels of security on it, depending on how sensitive the information is. It seems to me that especially nowadays, this study should have been relatively obvious. At any rate, if people are that concerned about privacy, they should take steps to conceal it themselves and not demand larger companies or the technology manufacturers be the ones responsible.

Paper reading #16: Classroom-Based Assistive Technology

References

Meg Cramer, Sen H. Hirano, Monica Tentori, Michael T. Yeganyan, Gillian R. Hayes. "Classroom-Based Assistive Technology". UIST '10 Proceedings of the 23rd annual ACM symposium on User interface software and technology.  ACM New York, NY, USA ©2010.

 Author Bios

Meg Cramer and Sen Hirano are both currently graduate students in Informatics at UC Irvine in the School of Information and Computer Science.

Monica Tentori is currently an assistant professor in computer science at UABC in Mexico, and is a post-doc scholar at UC Irvine.

 

Michael T. Yeganyan is an Informatics STAR Group Researcher at UC Irvine and hold an MS in Informatics.

Gillian R. Hayes is currently an assistant professor in Informatics in the School of Information and Computer Science at UC Irvine.  She also directs the STAR group.

Summary

• Hypothesis - The vSked system is an improvement over current systems to help autistic students in school.
• Method - There are three main stages in the development of vSked. During each stage, the teachers and aids were interviewed and asked to comment on the system. The students were not directly interacted with, as the demonstrated minimal communication skills. Several pieces of information were taken into account when evaluating the system, such as level of consistency and predictability in the schedule, student anxiety, and teacher awareness. The researchers analyzed data to ensure that the system was seeing to teacher and student needs.
• Results -The results were highly positive. The teachers expressed a large amount of surprise at some of the results. Students were able to learn concept much faster with the images given to them, as well as answer questions deemed too complicated due to the new system. Students were able to progress through the day's activities with much less prompting, and they were much more comfortable with the new calendar system.
• Content - This paper introduced the vSked system, which was engineered towards helping autistic students succeed in school. They tested it by introducing it to a class and interviewing the teachers about student progress and how well the students used the system. The results were positive across the board. It was noted that it was somewhat inflexible, but that it had a lot of room for changes.

 Discussion

Although I am not particularly interested in this kind of technology, this was a large step in a good direction. Helping these students succeed is a great goal. Instead of producing a new type of technology, their aim was to improve existing concepts and implementing them in a real-world environment. They were able to prove that their system was a large improvement over current systems, and it is highly possible this system will be used widely in the future.

Paper Reading #15: Madgets: actuating widgets on interactive tabletops

References

Malte Weiss, Florian Schwarz, Simon Jakubowski, and Jan Borchers.  "Madgets: actuating widgets on interactive tabletops". UIST '10 Proceedings of the 23rd annual ACM symposium on User interface software and technology.  ACM New York, NY, USA ©2010.

 Author Bios

Malte Weiss is currently a PhD student at the Media Computing Group.  His research focuses on interactive surfaces and tangible user interfaces.

Florian Schwarz is currently an assistant professor of linguistics at the University of Pennsylvania.  He received a PhD in Linguistics from the University of Massachusetts.

Simon Jakubowski is currently a Research Scientist at AlphaFix. He was a research scientist at the University of Texas Medical School in Houston. 

Jan Borchers is currently a professor at RWTH Aachen University.  He received a PhD in Computer Science from Darmstadt University of Technology.

Summary 

• Hypothesis - The researchers hypothesized that they could create small, light-weight physical widgets to be used on top of an interactive touch display that could modify the position of the widget.
• Method - The goal of this paper was to make an interactive tabletop that was low cost and light-weight. The realized this by using magnetic widgets and an electromagnetic array below the screen. They utilize infrared reflectors and sensors to classify a given widget and get its location. By changing polarities and strengths of the magnets below the display they are able to move the Madgets along a calculated path.
• Results - The researchers were able to construct their prototypes as well as several other types of widgets. The widgets themselves to not take long to build, although registering new controls can take considerably longer (up to 2 hours). The developers are currently working on a method to make the process faster to allow for rapid prototyping.
• Content - The authors of this paper presented Madgets, a method to integrate physical objects with the virtual world. They also demonstrated that the system can do much more with the widgets than just move them physically; they can alter their properties and make them perform much more complicated tasks, such as ring a bell or act as a physical button. The paper offers a complete description of how the system works and why it is beneficial.

 Discussion

All in all, I rather enjoyed this concept. Although it wasn't a research paper per se, it did hold some interesting ideas. While reading it I toyed with the idea of playing chess with a system such as this. This could also be useful for representing a military battle, physically representing troop movements without moving pieces inaccurately by hand. It also made me think of the hologram game in the original Star Wars movie (4th), which looked a little like chess but with monsters. Not quite the same concept, as that deals with holograms, but it did remind me of it.

Paper reading #14: TeslaTouch: electrovibration for touch surfaces

References

Olivier Bau, Ivan Poupyrev, Ali Israr, and Chris Harrison.  "TeslaTouch: electrovibration for touch surfaces". UIST '10 Proceedings of the 23rd annual ACM symposium on User interface software and technology.  ACM New York, NY, USA ©2010.

 Author Bios

The authors were all researchers at Disney Research, except for Chris Harrison who was a graduate student at Carnegie Mellon.

Summary 

• Hypothesis - The researchers hypothesized that electrovibration can be used as an effective method for haptic feedback on touch surfaces.
• Method/Content - Electrovibration was created by placing a transparent electrode layer between a glass plate and a thin insulation layer. Tests ensued to find human thresholds of what they could detect with their fingers. Ten participants were tested for thresholds in frequency and amplitude. They were also asked to describe the "feeling" of each level. After the user study was conducted, they developed several applications to show off their findings. 
• Results - Users found that higher frequencies led to smoother surfaces, low frequencies to rough surfaces. It was also found that the effect of amplitude depended upon the underlying frequency. Increasing amplitude for a high frequency increased the level of smoothness, where a low amplitude low frequency vibration induced a perception of stickiness. It was also noted that while users could feel the sensation of friction, they were able to perceive the vibration at the same time. 
• Content - The paper introduced TeslaTouch, a method of tactile feedback that does not require moving or mechanical parts. They tested different levels of electrovibration and categorized user perceptions. They then compared this new technology with existing mechanical feedback and discussed its advantages over the latter. They then discussed possible practical uses for this technology.

 Discussion

This technology seems to be very close in concept to an idea I had a long time ago for a screenless feedback device. This paper was very important to me in relation to that; it gave me a few ideas. Other than that, I loved the idea of this technology; I believe it can be very useful and it progresses us further towards virtual reality environments; can you imagine a full-body suit of electrovibrations that could allow you to feel different sensations on different parts of your body? It would be an amazing experience.

Paper Reading #8: Gesture Search: A Tool for Fast Mobile Data Access

References
Yang Li.  "Gesture search: a tool for fast mobile data access". UIST '10 Proceedings of the 23rd annual ACM symposium on User interface software and technology.  ACM New York, NY, USA ©2010.

 Author Bios
Yang Li received his Ph.D. from the Chinese Academy of Sciences and conducted postdoctoral research at the University of California at Berkeley. Li helped found the Design Use Build community while a professor at the University of Washington. He is now a Senior Research Scientist at Google.

Summary 

• Hypothesis -Yang Li theorized that some methods of phone input are inappropriate for some situations; for example, voice commands in a quiet environment is generally frowned upon. Also in some situations, touch-based typing is difficult to accomplish. The hypothesis is that Gesture Search is a better alternative to access mobile data.
• Method/Content - He developed an Android app that he made publicly available to the company (Google). The application logged user data and after a certain period was used to analyze performance. Users were not required to use it at any time and could stop using it when they wanted. However, when choosing which data to analyze, he required that the user used it at least once per week. Yang then set up a study in which he asked for users to perform certain actions on a mobile device using standard GUI interfaces. They were not told what the study was about so as to create a natural environment. 
• Results - After comparing the two types of mobile interactions, they hypothesis was supported in certain situations. Users typically used the Gesture Search for contacts, occasionally for apps, and very rarely for web pages. The majority of searches were found quickly, in under 3 seconds. The average rating for the app was 4/5 stars, with few outliers. Most users were happy with the app due to the ability to find information without going through a hierarchy of menus. 
• Content -  Yang Li developed an Android application that utilized gesture input to search through a smart phone for contacts, music, and other such information. He solves several problems of ambiguity by using a time-out method to decide whether a stroke is still the same letter. Also, he gives search results weights; when something is selected, its weight increases. With time, weights fade and they don't show at the top of the search results any longer. After developing the application, he studies people's usage of the application and compares it to GUI based operation.

 Discussion
I actually downloaded the app and used it for a while myself. It was useful occasionally, but mostly only when I was holding something in one hand. However, the biggest thing I didn't like about it was that it didn't search through files. That was the one thing I wanted it to do; finding a contact for me takes about 5 seconds anyway. However, going into a file manager, navigating through folders and scrolling through files can take a good bit of time, especially when there are many small files in the same folder. It seems to me that it would not take a huge amount of effort to extend this application to search through the phone's memory, so I was disappointed to find that it did not support this functionality.

Paper Reading #7: Performance Optimizations of Virtual Keyboards for Stroke-Based Text Entry on a Touch-Based Tabletop

References
Jochen Rick.  "Performance optimizations of virtual keyboards for stroke-based text entry on a touch-based tabletop". UIST '10 Proceedings of the 23rd annual ACM symposium on User interface software and technology.  ACM New York, NY, USA ©2010.

 Author Bios
Jochen Rick received his Ph.D. from Georgia Tech. He is currently a professor at Saarland University.

Summary 

• Hypothesis - The layout of a keyboard drastically influences user performance when using stroke-based input.
  
• Method/Content - The author originally created a mathematical model of user input performance in order to compare the performance of different keyboard layouts. He created this model by means of a user study in which he collected data such as the speed of strokes in different directions and turning speed. He was able to then create a visual representation of the data. Once he had this model, he was able to find constants for each equation that represented a good scaling potential. He then applied these equations to newly created keyboard based upon this information and the standard keyboards in use (such as QWERTY and Dvorak).
• Results - The results were as expected; the optimized keyboards outperformed the standard key layouts, although the standard key layouts are effective for tap-typing. He mentioned that it was expected as these layouts were designed for typing with ten fingers, where the compact layouts were designed with one fingered strokes specifically in mind.
• Content - The author claims that there is a need for more optimized keyboard layouts based around stroke-based input. He goes into the history of keyboard layouts and the reasons behind the development of the current most common ones. He then develops a model with which to compare keyboard layouts' efficiency. After developing this model, he compares optimized keyboards to current keyboards. He then proposed new keyboard layouts that show overall improvement over current layouts.
  

 Discussion
This paper seems pretty intuitive at every point, but it seems that no one had done a study specifically on it until now. However, I'm all about efficiency, so this held my interest pretty well. I personally tap-type, so I can't relate to the stroke-based typing; however, if a good keyboard layout were implemented for stroke typing, I may give it a try. It just seemed to me originally that if I were to use a standard keyboard layout why use a different input method? I was especially interested in the hexagonal layout; that is very different from the norm and look fun to try.

Paper Reading #6: TurKit: Human Computation Algorithms on Mechanical Turk

 References
Greg Little, Lydia B. Chilton, Max Goldman, and Robert C. Miller.  "TurKit: human computation algorithms on mechanical turk". UIST '10 Proceedings of the 23rd annual ACM symposium on User interface software and technology.  ACM New York, NY, USA ©2010.

 Author Bios
Greg Little is a graduate of MIT.

Lydia Chilton is a graduate student at the University of Washington.  She has interned for Microsoft Research in Beijing.  She is also a graduate of MIT.

Max Goldman is a professor at MIT and is part of the User Interface Design Group.

Rob Miller is also a professor at MIT.  Miller is the leader of the User Interface Design Group.

Summary 

• Hypothesis - The researchers hypothesize that using TurKit they can aid in the development of algorithmic tasks for mTurk at the cost of efficiency.
  
• Method/Content - They based their design on what they called the "crash and re-run" paradigm. This is an advanced implementation of dynamic programming; in essence, it allows the expensive functions to run only once and subsequent callings of the same function simply retrieves data stored in a database. Thus when the program crashes, the user can pick and choose which functions to run again, without needing to run the entire thing.
  
• Results - The results were overall positive. The main complaints were that the scripts TurKit could run needed to be deterministic, for if it were to change with different inputs it would need to be run again anyway. Another complaint was that some users did not know of some of the features, but this also may be that they were using it in the early stages of TurKit's development, when some had not been implemented yet. They did, however, discover that the running time of all of the TurKit script is faster than nearly all of the human function calls.
• Content - TurKit is a tool that automates mTurk for ease of use and repetition. It allows users to specify which parts of the program to rerun in the event of a crash. It goes in depth for some of the features. It also describes user reactions to TurKit.
  

 Discussion
The researchers successfully developed a useful tool to help with mTurk. Its crash and re-run design paradigm complements the slow human function runtimes very well. They did state, however, that while it is useful for research, it is doubtful that it will be useful in any large-scale project. While it is hard to say whether human computational resources are truly a valuable resource are not is up to mTurk, but TurKit is indeed a useful tool to be used with mTurk. I hope they can continue their development of TurKit so they may scale the tool for large-scale projects.

Paper Reading #5: A Framework for Robust and Flexible Handling of Inputs with Uncertainty

References
Julia Schwarz, Scott Hudson, Jennifer Mankoff, and Andrew D. Wilson.  "A framework for robust and flexible handling of inputs with uncertainty". UIST '10 Proceedings of the 23rd annual ACM symposium on User interface software and technology.  ACM New York, NY, USA ©2010.

 Author Bios
Julia Schwarz is a Ph.D. student at Carnegie Mellon University.

Scott Hudson is a professor at Carnegie Mellon University, where he is the founding director of the HCII PhD program.

Jennifer Mankoff is a professor at the Human Computer Interaction Institute at Carnegie Mellon University.  Mankoff earned her PhD at the Georgia Institute of Technology.

Andrew Wilson is a senior researcher at Microsoft Research.  Wilson received his Ph.D. at the MIT Media Laboratory and researches new gesture-related input techniques.
Summary 

• Hypothesis - The researchers hypothesized that using the uncertainty aspect of a gesture during the process to interpret it will give more accurate results.
  
• Method/Content - They created several examples to test their framework. It works by sending the user input to all possible recipients of the gesture, along with the information about it. When it sends this along, it also calculates the probability of it being the correct choice. However, the evaluation system used in this framework is lazy; that is, it waits until the last possible second to actually decide which action to take. Once the gesture or gesture sequence is completed (noted by specific actions, such as taking a finger off the screen or a specific length period of silence), it then by probability decides which action to take. One of the examples they used was voice recognition where 'q' and '2' sound the same.
  
• Results - All of their tests came out positive. The findings were that their system did increase the accuracy of interpretation by a large margin. The results from four movement impaired subjects with conventional motion gesture recognition was that between 5 and 20% of all inputs were interpreted incorrectly. However, with the new system, less than 3% for all four of them were misinterpreted.
• Content - The researchers first discuss the limitations of current gesture search systems. They put forth their claim that getting rid of uncertainties in the beginning of the system greatly increases the chances of misinterpreting a gesture. The then created a system in which it keeps these uncertainties and the associated information. Using this new system, they test several participants and compare the new system with the current one. They hypothesis was supported, and they go on to discuss future possible applications.
  

 Discussion
The thoughts of the developers were that rather than getting rid of uncertainties in the beginning when they have nothing else to go on, they should wait to get rid of them until the end when something inputted later may narrow down the choices. This is a surprisingly new concept that has not been strongly implemented yet. Especially in today's world where screens are getting smaller and touch-interaction is the norm, being able to select actions based upon probability is a must. This would be a great thing to integrate into many systems in use today, like smart phones and tablet PCs.

Paper Reading #4: Gestalt

References
Kayur Patel, Naomi Bancroft, Steven M. Drucker, James Fogarty, Andrew J. Ko, and James Landay.  "Gestalt: integrated support for implementation and analysis in machine learning". UIST '10 Proceedings of the 23rd annual ACM symposium on User interface software and technology.  ACM New York, NY, USA ©2010.

 Author Bios
Kayur Patel is a PhD student at the University of Washington specializing in machine learning.

Naomi Bancroft is a Senior undergraduate researcher at the University of Washington. Her interests lie in HCI.

Steven M. Drucker is a  Principal Researcher at Microsoft Research with who specializes in HCI. He received his PhD from MIT.

James Fogarty is currently an assistant professor at UW. His research focuses on HCI and Ubiquitous computing. He received his PhD from Carnegie Melon.

Andrew J.Ko is also currently an assistant professor at UW. His research focuses on the “Human aspects of software development”. He also received his PhD from Carnegie Melon.

James A Landay is a professor at UW, whose research focuses on Automated Usability Evaluation, Demonstrational Interfaces, and Ubiquitous Computing. He received his PhD from Carnegie Melon as well.

Summary 

• Hypothesis - A general purpose Machine Learning tool that allows developers to analyze the information pipeline will lead to greater efficiency and fewer errors.
• Method/Content - The researchers created two problems, one for movie reviews and one for gesture recognition. Eight testers were then given a program for each problem; each program had 5 bugs in it. Within an hour, they were asked to find and fix as many bugs as they could. The tools they used to find and fix these problems were their newly developed Gestalt Framework, and the other was to use a customized version of Matlab. Each participant was asked to solve each problem with each program (4 tests in all).
• Results - The results showed that participants were able to find significantly more errors while using the Gestalt framework. Some even tried to create Gestalt functionality within Matlab. All eight of the users preferred Gestalt over Matlab, and most of them stated that they would likely benefit from using Gestalt in their work. 
• Content - This paper presented Gestalt, which is a new tool for developers of Machine Learning. It then conducted a user study to compare it with other similar software, and found that it was indeed a good tool. It then discussed its strengths and weaknesses. Its main strength lies in its ability for users to view the information pipeline.

 Discussion
Although a general purpose tool cannot necessarily perform all of the same tasks as well as a domain-specific tool, they are often flexible enough to still be a powerful tool. Gestalt seems as if it has a good ways to go before it sees general use, but the results were promising. Throughout the paper, the greatest thing that I saw about the framework was its ability to let you view (and manipulate) the information pipeline. This is key for many applications, especially machine learning. Although their testing methods were not robust, they did serve to show a general sentiment of how Gestalt can be useful to developers.

Paper Reading #23: User-Defined Motion Gestures for Mobile Interaction

References
Jaime Ruiz, Yang Li, Edward Lank.  "User-Defined Motion Gestures for Mobile Interaction". UIST '11 Proceedings of the 2011 annual conference on Human factors in computing systems.  ACM New York, NY, USA ©2011.

 Author Bios
Jaime Ruiz is a fifth-year doctoral student in the HCI Lab at the University of Waterloo. His main research interests is further understanding users to augment the level of human computer interaction. For this paper he was a research intern at Google Research.

Yang Li is a senior research scientist at Google Research. Before joining Google, he was a research associate in the Computer Science and Engineering at the University of Washington, where he helped found the DUB. He received his Ph.D. in Computer Science from the Chinese Academy of Sciences, and conducted postdoctoral research in EECS at the University of California at Berkeley.

Edward Lank is an assistant professor at the University of Waterloo. Before he joined Waterloo, he was an assistant professor at San Francisco State University and conducted postdoctoral research at Xerox. He received his Ph.D. in Computer Science from Queen's University.

Summary 

• Hypothesis - Conducting an end-user design test will result in best practices for designing gestural interfaces.
• Method/Content - This paper focused on a user study involving motion gestures using mobile phones. Twenty participants were involved. Because learning about a new device would have cause people to be less receptive to new concepts, they required that the participants used a smartphone as their primary mobile device. Nineteen tasks were given to the participants. For each task, the participant was asked to come up with an easy and comfortable gesture to conduct the desired action. For example, to come up with a gesture for answering a call. Because they did not not want users to focus needlessly on recognizer issues or the current level of technology, they asked participants to treat the device as a "magic brick", capable of automatically understanding and recognizing anything they might throw at it (figuratively, of course). The participants were asked to conduct the study while thinking aloud. In other words, they wanted the users to explain what they were doing, what they may be emulating, and why for each gesture. Once the participant had decided on a unique gesture for each of the 19 tasks, they were asked to perform each one five times. While they conducted each gesture the phone recorded data from the accelerometer and its other motion-detecting hardware and sent to another computer. Once they were done, the users were asked to rate their own gestures on a Likert scale based on its ease of use and whether or not they would use it often.
• Results -The results were that the closer a gesture was to emulating a real world object, the more of a consensus among participants was reached. For example, when answering a call, easily the most common gesture was to simply raise their phone to your ear. This makes sense, as for a normal call, this would be the first thing you do (usually after you answer it). An example of emulation that does not happen regularly is the act of hanging up the phone. The gesture users found the most consensus on this one was to emulate an "old-fashioned" phone; that is, they turned the phone so that its screen was parallel to the ground. Another thought that many users had is that some of the actions should have the same gesture; for example, going to the next photo, contact, or search results, it should all be a flick to the right. Users generally agreed that although in different contexts, the end result was basically the same, so the same gesture should be used. For actions that did the opposite of another, users generally performed the same gesture, only in the opposite direction. For example, going to the previous item in a list required a flick to the left. Another example is zooming in and out on a map; zooming in was to bring it closer to your face, zooming pushing it farther away.
  
  Another curious result is that, in contrast to surface gestures, users generally wanted to move the window as opposed to the object. This means that when dealing with a map or image, the users panned left by moving the phone to the left, whereas with a surface gesture it is moving to the right. This was explained by the fact that when touching the screen itself, the user was in effect moving the object on the screen. However, when moving the phone, the user was moving the screen around the object, and expected it to react as such.

 Discussion
This paper seemed like it is a bit late in coming, although I enjoyed it. It seems that we have had the technology for a long time, and it took us this long to start looking for motion gestures? I remember back when the Gameboy Color was popular; Kirby Tilt 'n' Tumble was one of my favorite games. That used an accelerometer, which is one of the main tools used in motion gestures. It just surprised me that it took us this long to make the transition. However, I think that this technology/concept has a large range of practical applications. Things like conducting presentations or interacting with colleagues in a design room would be great places to use a device for this. However, this could also raise the problem of using a phone in the car, which we already have enough issues with. As seen in Why We Make Mistakes, making the phone accessible without looking at it would not solve the problem. Humans simply cannot multitask that well.

Paper Reading #13: LightSpace

References
Andrew D. Wilson, Hrvoje Benko.  "Combining Multiple Depth Cameras and Projectors for Interactions On, Above, and Between Surfaces". UIST '10 Proceedings of the 23rd annual ACM symposium on User interface software and technology.  ACM New York, NY, USA ©2010.

 Author Bios
Andrew D. Wilson is a senior researcher at Microsoft Research. He received his bachelor's from Cornell, and subsequently his master's and Ph. D. at MIT. He helped found the Surface Computing group at Microsoft.

Hrvoje Benko is also researcher at Microsoft. He received his Ph.D. from Columbia University. His  interests revolve mostly around augmented reality and in discovering new ways to blur the line between 2D computing and our 3D world.

Summary 

• Hypothesis - This paper did not have a hypothesis; it was simply a discussion and description of a design concept.
• Method/Content - The main concept behind this design was to allow users to interact with projected displays using normal tables (or other ordinary flat surfaces) as touch-screens. It made use of a suspended apparatus containing 3 IR and depth cameras and 3 projectors. The device decided what the user was doing by creating a 3D mesh of them and simulating their movements in a virtual 3D space. It created the mesh by using its cameras to create depth maps from different angles. Because it used the notion of one virtual space for all 3 cameras and projectors, there was no real discrepancies or major mistakes in gesture recognition. Available interactions included dragging some projected object off of a table, holding said object, putting the object back on the table (or a different one), moving objects from table to vertical screen and back, transferring objects from one person to another, and an interactive menu. The menu worked by moving through options based upon the height of the users hand, and selecting it if the user held it there for 2 seconds. Holding an object worked loosely on the idea of holding a ball; the user held their hand level and carried the "ball" where the wanted it to go. They could let go and drop the ball at any time.
• User feedback on this system was overall very good. During their public demonstration they discovered a number of limitations that were not readily apparent, but were possible to fix. One of the limitations was that if there were more than 6 people in the room, the system would get confused as to who was who because everyone was too close to one another. It was hard for the system to distinguish what person was trying to perform what action. This is easily enough fixed by increasing the space in the room and the range of the cameras/projectors. Another limitation found was that having 3 or more people in the room slowed the system drastically; the refresh rate of the system (and thus the projectors) dropped below the camera's refresh rate. This is also pretty easily fixed, to a point: use a more powerful computer to render the 3D space and meshes used. There is obviously an upper bound on the amount of people the system can accommodate (due to both size constraints and computing power) but it can definitely perform better than what has already been implemented.

 Discussion
Again, I loved this paper. It seems that the more I read, the more I realize that we are much closer to virtual reality environments than I thought. This system has a huge range of applications, from meetings to showcases, from artists to engineers, from product design to video games. The concept of moving objects from one surface to another is not really what excites me; it's the system itself. The fact that they can use relatively simple and inexpensive cameras to track multiple entities without the users wearing external apparatus (ie dots or markers) is amazing. I would absolutely love to have this system in my house, if just to play around with and maybe customize (to perform different actions).

On Gangs

Sudhir's Gang Leader for a Day was a very interesting book. I thoroughly enjoyed all but the last few pages. In those pages, I was really disappointed that he said they had never been friends. It seems to me that when you go through that many things together for that long and still enjoy being around one another, you have become friends. Even to this day, Sudhir visits JT whenever he is in Chicago; that says friend to me. I suppose he needed to say that (according to lawyers) in order to acquit himself and show that he is and was not associated with any gangs, but it still seems to be a terrible way to end the book.

During the book, it astounded me to see what the people living in the projects did and endured to survive, especially the women. Some of the things they did I had previously associated with third world countries; that it was happening here in the US and especially in one of the most influential cities made me sad. Although thinking about it now, I suppose it should not have come as a surprise; you'll find poverty anywhere.

When Sudhir was a gang leader for a day, I felt that he embellished on a lot of it. I think that his decision about the guy who stole and the guy who withheld pay was correct; but it still wasn't his decision in the end. Throughout the day he was sort of riding shotgun instead of driving; JT would do most things and occasionally ask what Sudhir thought, then took it as advice rather than as instruction. There are reasons he couldn't truly make any of the final decisions: JT couldn't afford to lose face in front of his subordinates, if he made a wrong decision it could cause the loss of a lot of money, etc. But I still don't think 'gang leader for a day' is a proper description for what he did; 'gang leader adviser for a day' is a much more apt description.

When the projects were torn down, I felt bad for JT and his two long time friends. Yes, they were gang leaders and yes, they were perpetuating the use of drugs, but they truly believed that what they were doing helped the community as a whole (or so they claimed). Although they were perhaps rough about it and obtained the money for it through unethical means, they did what they needed to to survive; with those methods they also helped the community in many ways, whether or not they had an ulterior motive for it. I felt really sad when T-bone died; he truly had a plan for after the gang life. He wanted to get a degree, live normally and honestly. He seemed to me one of those that truly got caught up in something they didn't want and couldn't get out.

All in all, I really enjoyed the book. Sometimes sad, sometimes happy, but most of the time just interesting. The end was disappointing, but that by no means made it a bad book. I would definitely recommend this book for the future classes. 

Paper Reading #12: Enabling beyond-surface interactions

References
Thomas Augsten, et al.  "Enabling Beyond-Surface Interactions for Interactive Surface wit An Invisible Projection". UIST '10 Proceedings of the 23rd annual ACM symposium on User interface software and technology.  ACM New York, NY, USA ©2010.

Author Bios
Li-Wei Chan is a Ph. D. student in the Graduate Institute of Networking and Multimedia at the National Taiwan University. He received his master's and bachelor's in Computer Science from the National Taiwan University and from Fu Jen Catholic University respectively.

Hsiang-Tao Wu, Hui-Shan Kao, and Home-Ru Lin are students at the National Taiwan University.

Ju-Chun Ko is a Ph. D. student at the Computer & Information Networking Center, National Taiwan University. He got his master's in Informatics from Yun Ze University.
Mike Y. Chen is a professor in the Department of Computer Science at National Taiwan University. His research interests lie in mobile technologies, HCI, social networks, and cloud computing.

Jane Hsu is a professor of Computer Science and Information Engineering at National Taiwan University. Her research interests include intelligent multi-agent systems, data mining, service oriented computing and web technology.

Yi-Ping Hung is a professor in the Graduate Institute of Networking and Multimedia at National Taiwan University. He received his bachelor's from National Taiwan University and his Master's and Ph.D. from Brown University.

Summary

• Hypothesis - Using IR (infrared) cameras to place invisible markers will improve reliability for interactive tabletops.
• Method -For this experiment, they used a custom interactive tabletop prototype. It projected both color and IR from under the table, and used two IR cameras under the table to detect touches. The IR projector also selectively projects white space on the tabletop to perform multi-touch detection. The tabletop itself is comprised of two layers: a diffuser layer and a touch-glass layer. Due to the reflective nature of the touch-glass, it caused problems whether it was above or below the diffuser layer. They found that when it was above, it reflected the visible light of projections from above the tabletop, which caused not only a degrade in the luminance of the projection, but also shined the light on observers. When the glass was under the diffuser layer, it partially reflected the IR rays from beneath the table, resulting in dead zones for the image processing. They found that they could fix the dead zone problem by using two IR cameras instead of one, so they implemented the table with the touch-glass underneath the diffuser layer. The IR cameras used a dynamic sizing system to track projections and move/resize markers as needed. The proposed 3 different projection systems: the i-m-Lamp, the i-m-Flashlight, and the i-m-View. The first was a combination pico-projector/IR camera which appeared as a simple table lamp. Its small dimensions were thought to be ideal for integration with personal tabletop systems. The second (i-m-Lamp) implementation proposed is a mobile version of the i-m-Lamp. Users can inspect fine details of a region by focusing the i-m-Flashlight at the desired location. The i-m-View is a tablet PC attached to an IR camera. The programmed use for it was to intuitively explore 3D geographical information. They used the i-m-View to explore 3D buildings from above a 2D map shown on the prototype tabletop system. They asked 5 users to try out their systems and were encouraged to think aloud.
• The main problems found for the i-m-Lamp was that because the i-m-Lamp and the tabletop system both project on the same surface, the overlapped region caused a blue artifact. To avoid it, they masked the tabletop projection where the projections overlapped. For the i-m-Flashlight, they encountered a focus problem; the lens focus of the pico-projectors needed to be manually focused. This limited usability; however, they proposed that replacing the projector with one that contains a laser (such as the Microvision ShowWX) would provide an image that is always in focus. The largest problem with the i-m-View was that it was easy for users to get lost in the 3D view and not be able to pay as much attention to the 2D map. They fixed this by showing the boundaries of the 2D map inside the 3D view, allowing the user to simultaneously see what was changing on the table and what it represented in the 3D view. During for the i-m-View users often found that the buildings in the 3D view were too tall for the view; they wished to either pan up or rotate the tablet in order to get a portrait view of the landscape, neither of which were currently supported by the system. Another problem was that they i-m-View occasionally got lost because no IR markers entered its field of view; this was dealt with by continuously updating the orientation of the i-m-View. The overall feedback from users was positive, and the problems discussed are supposed to be addressed in future work.

Discussion
Quite frankly, I found this entire paper awesome. I thought that much of it was quite advanced, a huge step in HCI. While it may not have much application for me personally (I can't readily see this augmenting programming in many ways), it would have huge impacts on artists, the military, modelers and designers, engineers (such as civil or mechanical) and many more. Artists could use it to selectively edit only certain portions of their work without using the cumbersome selection methods used in today's art development programs. The military could quite easily use this for strategic purposes such as battle maps or location coordination. Modelers and engineers could use this to select certain pieces in a 3D model or blueprint to edit. In short, this technology has a huge range of applications that would make great use of it. I hope to see this technology distributed widely soon.

Paper Reading #11: Multitoe

References
Thomas Augsten, et al.  "Multitoe: high-precision interaction with back-projected floors based on high-resolution multi-touch input". UIST '10 Proceedings of the 23rd annual ACM symposium on User interface software and technology.  ACM New York, NY, USA ©2010.

Author Bios
Thomas Augsten, Konstantin Kaefer, are a master student of IT systems at Hasso Plattner Institute (University of Potsdamn) in Germany.

Christian Holz is a Ph. D. student in Human Computer Interaction at the Hasso Plattner Institute. He believes the only way to continue to further miniaturize mobile devices is to fully understand the limitations of human computer interaction. 

Patrick Baudisch is a professor in Computer Science at the Hasso Plattner Institute.

Rene Meusel, Caroline Fetzer, Dorian Kanitz, Thomas Stoff, and Torsten Becker are students at the Hasso Plattner Institute.

Summary

• Hypothesis - Using foot input is an effective way to interact with a back-projected floor based computer.
• Method - The first study conducted was intended to be built off of for subsequent experiments. It was to test how buttons could be intentionally walked over without activating them. Participants were asked to walk over 4 buttons, two of which were meant to be activated, 2 of which were not. User methods were recorded and categorized. The second study determined which area of the foot user expected to be detected to activate a button. The third study was to determine if there was consistency in preferred hotspots across the user base. The fourth was meant to determine user ability; they were asked to type a sentence using a projected keyboard.
• The results for the first test were that users did not generally have a consistent way to activate buttons. In the second test, most users agreed that the foot's arch was the best way to activate a button. The third test showed that users had virtually no agreement between users; no hotspots had the majority of usage. In the fourth test, it was found (as expected) that the smaller the keyboard, the more errors the user made. Users were about even in their preferences of the medium and large keyboards.

Discussion
While I'm not sure that this technology has immediate application, I believe that this could be one of the first steps to virtual reality rooms. I really enjoyed the concept, although I'm not sure that the users enjoyed it as much as me. Current uses may be exploring maps, or games such as Dance Dance Revolution, or if they include multi touch (with a large amount of possible touches) it could support group activities or games.

Paper Reading #10: Sensing Foot Gestures from the Pocket

References
Jeremy Scott, et al.  "Sensing Foot Gestures from the Pocket". UIST '10 Proceedings of the 23rd annual ACM symposium on User interface software and technology.  ACM New York, NY, USA ©2010.

Author Bios
Jeremy Scott received his Bachelors in Computer Engineering from the University of Toronto and is working toward a Ph.D. in Computer Science from MIT. He was an undergraduate researcher at U of T and is now a research assistant at MIT.

David Dearman is a Ph.D. student at University of Toronto. His research interests lie in combining HCI, Ubiquitous computing, and Mobile computing.

Koji Yatani is a Ph. D. student at the University of Toronto. His research revolves around HCI and Ubiquitous computing, with an emphasis on hardware and sensing technologies.

Khai N. Truong is a professor at University of Toronto. His main interests lie in HCI and ubiquitous computing, revolving around enhancing usability and usefulness of mobile technology.

Summary

Hypothesis - A mobile device placed in a pocket of a person's pants can recognize simple foot gestures using the built-in accelerometer.

Method - For this paper, two experiments were conducted. The first used 16 right-footed individuals (8 male, 8 female). They were given specific angles to rotate their feet at (in four different ways, as seen below).

The researchers recorded the accuracies of each angle as well as the amount of time it took for a user to confidently position their foot. After comparing all of this research, they then designed a system for the iPhone using the accelerometer to sense the foot gestures. A user would double tap their foot (average of about 330 milliseconds apart) and subsequently execute at gesture (rotating their foot a certain way to a range of angles). They used 6 ranges of angles, 3 clockwise and 3 counter (from natural foot position). This experiment used 6 right-footed participants, 4 male and 2 female.

Results - The results were relatively successful. Their system could determine about 10 different foot gestures with 86% accuracy. They determined that with this system it is possible to augment user experience.

Discussion
I found this article to be really interesting. I have a particular interest in gestures that aren't based on visual feedback or physical manipulation of technology. This seems to be a good step in that direction. I'm not sure if foot gestures can really be read accurately enough to make it be a viable replacement for other similar gestures, but this is definitely a good stepping stone.

Ethnography - Point 1

In the past couple of semesters, I have taken the fencing class but have never actually hung out with anyone who does it seriously. I already knew from experience that there is a huge difference, as I took a couple archery classes and then proceeded to join the club. The culture change between those who signed up for the classes and those who have done it for years (some of them professionally) was complete. So, I decided that I would join the fencing club as my ethnography project.

We (Andrew Funderburgh and I) actually planned to go to their meeting on Monday, but ended up being there early. We found the room completely empty, so we went downstairs to ask the people at the front desk (ish, more of just a window where they look at your id before you can go in) where the fencing club was supposed to meet and where. We figured that maybe their website was simply outdated. However, when we talked to those at the front, they told us that fencing was never scheduled to be in that building at all. Thus, having no contacts, we were forced to drop it for the day.

The next day, in fencing class, I asked the teacher when they were supposed to meet. He told me that it was where and when we thought it was. One of the other people in the class, who also happens to be in the club, told me that they just happened to be running late Monday. Unlucky.

So, Wednesday comes around and we try for a second round. When we get there, there were only a couple of people waiting. We sat on the floor and waited for things to get running. When the club president came in, he promptly gave us forms to fill out for rec sports so that we could be allowed to fence, basically just a liability form. There hadn't been much conversation between the few people who were there or with us, but it wasn't precisely awkward.

Having fenced before, I was "allowed" to participate in the conditioning that happens before every practice. During this, the only thing I could get my mind to learn was the fact that I am terribly out of shape. At any rate, during drills people talked more or less amongst themselves, occasionally shouting across the room to someone in another conversation. The conversations were mostly banter, nothing about fencing or really anything in particular. They all seemed to know each other extremely well.

After conditioning, I went with a few people down to the "armory", which is where spare equipment is kept. I had no clue where everything was, so I had to keep asking questions. Except for my questions, we talked mostly about dancing of all things (we passed a dancing club on the way there).

During the actual fencing, everyone was serious and very much participating at the height of their prowess. This was highly unusual for me, for during the classes there's hardly ever 5 minutes without a joke cracked. The fact that everyone was giving their all was also somewhat unusual; during the classes, those who are better than others tend to hold back when fencing. It A) gets boring to those who are good and frustrating for those who are not, and B) doesn't give the other people a chance to learn. In the club, it was clear that I was somewhat on my own. They gave me advice on my techniques when we were done with our bout, but during it was all work and no play. The level at which these people were at also took me off guard; I've usually been somewhere near the top during the classes, but in the club I am definitely low-tier. Some of them moved so fast I literally did not see them in time to react.

In all, it was a fun first time. The people were very open and talkative. They were helpful and instructive (when not fencing). Doing an ethnography on these guys will be interesting, if tough. I am definitely bringing a gigantic water bottle next time.

Paper Reading #9: Jogging over a Distance between Europe and Australia

References
Florian Mueller, et al.  "Jogging over a Distance between Europe and Australia". UIST '10 Proceedings of the 23rd annual ACM symposium on User interface software and technology.  ACM New York, NY, USA ©2010.


Author Bios
Florian Mueller is an avid athlete and advocator of sports. His main work focuses on the social and physical effects of integrating technology and exercise. He has researched with many institutions including Stanford University, MIT Media Lab, Media Lab Europe, Microsoft Research and many others.


Frank Vetere has several degrees, among them a bachelor's in science and a doctorate in philosophy, both from the University of Melbourne. His research interests are in Human Computer Interaction and Interaction Design. He is currently a professor at the University of Melbourne and works with the Interaction Design Group.


Martin R. Gibbs has a Ph. D. in sociology and is currently a lecturer at the University of Melbourne. His main research interests are in design space and intergenerational play.


Darren Edge received his bachelor's and Ph. D. in Computer Science from the University of Cambridge. He is currently a researcher at Microsoft Research based in Beijing. His main interests lie in how to combine abstract analysis, user research, and design thinking in order to further HCI.


Stefan Agamanolis holds a master's and a doctorate in Media Arts and Sciences from MIT. He is currently the Associate Director of the Rebecca D. Considine Research Institute at Akron Children's Hospital. His research interests revolve around experience design for healthcare scenarios.


Jennifer Sheridan has a Ph.D. in Computer Science and a Master's in Human Computer Interaction. She is currently the Senior User Experience Consultant and Director of User Experience at BigDog Interactive.

Summary

• Hypothesis - Focusing on the user experience of engaging systems that integrate technology and social exertion will contribute to the knowledge of the underlying elements involved.
• Method - In this experiment, two people plan to jog at the same time (GMT). Both of them are wearing a headset, a heart monitor, a mini computer and a mobile phone. Based upon a set goal heart rate (chosen before the running begins), the audio from the other person is projected to the user from a different virtual location. For example, if they are both running at the same percentage of the targeted heart rate, they will both hear each other as if they were running side by side. However, if one person's heart rate goes beyond their goal and the other's stays at it, the sound from the first person will be coming from in front of the second (as if the first were running faster and was getting ahead). On the first person's end, it would appear to them that the second person is behind them; thus the users are able to judge how much effort they are putting in compared to their running partner. 
• Their results were successful; the technology turned the exercise into a social activity, thus increasing user engagement. They conclude that their hypothesis was correct, that they did indeed come out of this with a better understanding of what may go into social exercise. 

Discussion
This article didn't really reach me personally. I do agree that exercise is better and more immersive when done socially, but don't we already have sports for that? I can't stand running, mostly because I find it intensely boring. Perhaps this may help develop something that would make running more fun for me, but in order to get proper exercise, I can just as easily turn to soccer or fencing or some other group sport (it would be a lot cheaper, too). To be frank, I think this is a study more suited for people fighting obesity and less for people aiming to create future human computer interaction; this, in my opinion, was entirely human-human even though it used technology to bridge a distance.