Alvin Jude

Bimanual Word Gesture Keyboards for Mid-air Gestures

Mid-air hand gestural interaction has generally been researched as a pointing device. However, recent research has shown potential for text input with the use of word gesture keyboards (WGK), where these forms of interactions require the input system to identify when the gesture has started and when it has stopped. Previous research has had success where the same hand moved the cursor, and performed the activation gesture. In this paper we introduce bimanual interaction for gestural interaction to perform text input with WGK, where one hand moves the cursor while the other hand performs the activation. In our user studies, the bimanual method demonstrated significantly higher results than the state-of-the-art single handed method. We achieved 16 words per minute; about 39% higher than the benchmark, and with significantly lower error rates.

Improving Gestural Interaction With Augmented Cursors

Gesture-based interaction has become more affordable and ubiquitous as an interaction style in recent years. One issue with gestural pointing is the lack of accuracy with smaller targets. In this paper we propose that the use of augmented cursors - which has been shown to improve small target acquisition with a standard mouse - also improves small target acquisition for gestural pointing. In our study we explored the use of Bubble Lens and Bubble Cursor as a means to improve acquisition of smaller targets, and compared it with interactions without them. Our study showed that both methods significantly improved target selection. As part of our study, we also identified the parameters in configuring Bubble Cursor for optimal results.

Reporting and Visualizing Fitts's Law: Dataset, Tools and Methodologies

In this paper we compare methods of reporting and visualizing Fitts regressions. We show that reporting this metric using mean movement time per user over accuracy-adjusted Index of Difficulty (IDe) produces more descriptive visualization. This method displays variance, which is more useful in understanding the interfaces, than an aggregated means-of-means approach using Index of Difficulty. We demonstrate that there is little difference in slope and intercept between the two methods, but has the potential to uncover wider goodness-of-fit coefficients which could allow for better comparison across experiments. We propose the use of quantile regression to report central tendencies as a trend, rather than box plots. The tools released with this paper can be used with any pointing device evaluation done with the FittsStudy program. The dataset released with this paper contains almost 25,000 samples, which can be used in future research for reporting or visualizing Fitts regressions.

Modeling Mid-air Gestures With Spherical Coordinates

Generally, touchless mid-air gestural interaction use some form of Cartesian coordinate system within the input space. Most implementations map the input space in 3-D and map it to the 2-D of the monitor for output. In our previous work we showed that modeling the interaction space produces better interaction [1]. In this study, we use the Myo armband to show that a modeled interaction space also benefits devices that use spherical coordinates.

I don't need to see that: Seeking, Avoiding, and Attempting to Control Video Content

Evolving technology and growing connectedness of devices allow more opportunities for video consumption, and greater integration in our everyday activities. This study conducts exploratory research on video interaction to better understand how people currently seek, avoid, and attempt to control video content. Data was collected by a semi-structured interview process with 10 participants. Three interesting trends emerged in peoples video watching behavior: (1) Social context and obligations change behavior, (2) a preference for more participatory parental monitoring techniques, and (3) the importance of storyline in video viewing behavior. These findings can help inspire future research, and help designers and technologists recognize the complexities and dynamic nature of how people watch and attempt to control their video content. Designing with this knowledge can improve users» experience when they consume media content in the form of videos.