My colleagues, Radu-Daniel Vatavu and Quincy Brown, and I, have combined our efforts on exploring touch interaction for children on a paper which has been accepted to the INTERACT 2015 conference! The paper, titled “Child or Adult? Inferring Smartphone Users’ Age Group from Touch Measurements Alone,” showed the results of our experiments to classify whether a user is a young child (ages 3 to 6) or an adult from properties of their touch input alone. Radu used his dataset of 3 to 6 year olds and supplemented with our MTAGIC dataset. The abstract is as follows:
We present a technique that classifies users’ age group, i.e., child or adult, from touch coordinates captured on touch-screen devices. Our technique delivered 86.5% accuracy (user-independent) on a dataset of 119 participants (89 children ages 3 to 6) when classifying each touch event one at a time and up to 99% accuracy when using a window of 7+ consecutive touches. Our results establish that it is possible to reliably classify a smartphone user on the fly as a child or an adult with high accuracy using only basic data about their touches, and will inform new, automatically adaptive interfaces for touch-screen devices.
You can download the camera-ready version of the paper here. Radu will be presenting our work at INTERACT, which will be held in Bamberg, Germany, in September. I’ll post the talk when available!
The ACM International Conference on Multimodal Interaction, was recently held in Istanbul, Turkey. My co-author Radu-Daniel Vatavu presented the poster for our paper entitled “Gesture Heatmaps: Understanding Gesture Performance with Colorful Visualizations,” which you can check out here. I was sorry not to be able to attend this year, but perhaps next year (it will be in Seattle, WA).
My colleagues, Radu-Daniel Vatavu and Jacob O. Wobbrock, and I have had another paper accepted for publication! This paper continues our efforts to understand patterns and inconsistencies in how people make touchscreen gestures. This time, we introduced a way to use heatmap-style visualizations to examine articulation patterns in gesture datasets, and our paper “Gesture Heatmaps: Understanding Gesture Performance with Colorful Visualizations” was accepted to the ACM International Conference on Multimodal Interaction, to be held in Istanbul, Turkey, in November 2014. Here is the abstract:
We introduce gesture heatmaps, a novel gesture analysis technique that employs color maps to visualize the variation of local features along the gesture path. Beyond current gesture analysis practices that characterize gesture articulations with single-value descriptors, e.g., size, path length, or speed, gesture heatmaps are able to show with colorful visualizations how the value of any such descriptors vary along the gesture path. We evaluate gesture heatmaps on three public datasets comprising 15,840 gesture samples of 70 gesture types from 45 participants, on which we demonstrate heatmaps’ capabilities to (1) explain causes for recognition errors, (2) characterize users’ gesture articulation patterns under various conditions, e.g., finger versus pen gestures, and (3) help understand users’ subjective perceptions of gesture commands, such as why some gestures are perceived easier to execute than others. We also introduce chromatic confusion matrices that employ gesture heatmaps to extend the expressiveness of standard confusion matrices to better understand gesture classification performance. We believe that gesture heatmaps will prove useful to researchers and practitioners doing gesture analysis, and consequently, they will inform the design of better gesture sets and development of more accurate recognizers.
Check out the camera ready version of our paper here. Our paper will be presented as a poster at the conference, and I’ll post the PDF when available.
Master’s student Karen Rust recently presented our poster “Understanding Child-Defined Gestures and Children’s Mental Models for Touchscreen Tabletop Interaction” at the Interaction Design for Children (IDC) conference, in Aarhus, Denmark. Check out the poster here. We’re looking forward to IDC 2015 in Boston, MA!
Last week at the ICMI 2013 conference in Sydney, Australia, I presented work done in collaboration with my co-authors Radu-Daniel Vatavu and Jacob O. Wobbrock on new ways of understanding how users make stroke gestures (for example, with stylus and finger on touchscreen devices), through the use of 12 “Relative Accuracy Measures for Stroke Gestures” that our paper introduced. The paper has details on the measures themselves and how they are derived; the talk focuses on what these types of measures can be used for and how they can help us design and build better gesture interactions. For those interested, my presentation slides are available here.
We have also released an open-source toolkit, which we call “GREAT” (Gesture RElative Accuracy Toolkit) that you can use to compute the measures on your own dataset. Download it here!
The $-family of gesture recognizers project has been working on more ways to characterize patterns in how users make gestures, in the form of new gesture accuracy measures (see our GI 2013 paper for the first set of measures we developed). This new set focuses on relative accuracy, or degree to which two gestures match locally rather than just simply global absolutes. Our paper introducing these measures has been accepted to ICMI 2013! My co-authors are Radu-Daniel Vatavu and Jacob O. Wobbrock. Here is the abstract:
Current measures of stroke gesture articulation lack descriptive power because they only capture absolute characteristics about the gesture as a whole, not fine-grained features that reveal subtleties about the gesture articulation path. We present a set of twelve new relative accuracy measures for stroke gesture articulation that characterize the geometric, kinematic, and articulation accuracy of single and multistroke gestures. To compute the accuracy measures, we introduce the concept of a gesture task axis. We evaluate our measures on five public datasets comprising 38,245 samples from107 participants, about which we make new discoveries; e.g., gestures articulated at fast speed are shorter in path length than slow or medium-speed gestures, but their path lengths vary the most, a finding that helps understand recognition performance. This
work will enable a better understanding of users’ stroke gesture articulation behavior, ultimately leading to better gesture set designs and more accurate recognizers.
I’ll be at ICMI 2013 in Sydney, Australia, in December (summer down under!) to present the paper. Come ask me about the details! In the meantime, check out the camera-ready version of our paper here.
This past week the Interaction Design for Children (IDC) conference was held in New York City! It was a great conference on lots of cutting edge research and design work being done in the area of children interacting with technology, ranging from exercise games to educational applications to kids with special needs. There were also great demos of some of the exciting projects.
I presented a paper on the MTAGIC project’s findings related to the impact of visual feedback on gesture interaction for kids. For those interested, check out the slides. UMBC PhD student Germaine Irwin presented the MTAGIC project’s poster on the use of gamification elements to encourage children to stay focused during empirical studies. She did a great job on the madness-talk (only 15 seconds!) and discussing the poster with interested people.
Next year IDC 2014 will be held in Aarhus, Denmark, home of LEGO!