This summer, I have been working on a project related to the $-family of gesture recognizers. The $-family is a series of simple, fast, and accurate gesture recognizers designed to be accessible to novice programmers. $1 [1] was created by… Read More

In our last post, we shared that we had a paper accepted to the ACM International Conference on Multimodal Interaction (ICMI) 2017, to be held in Glasgow, Scotland, UK. The paper was titled “Comparing Human and Machine Recognition of Children’s… Read More

In a previous post, we discussed our ongoing work on studying children’s gestures. To get a better idea of the target accuracy for continuing work in gesture recognition, we ran a study comparing human ability to recognize children’s gestures to… Read More

In previous posts, we have discussed our ongoing work on improving recognition of children’s touchscreen gestures. My paper, “Human-Centered Recognition of Children’s Touchscreen Gestures”, was accepted to ICMI 2017’s Doctoral Consortium! The paper focused on my future research plans as I… Read More

We are currently continuing our work in gesture recognition by studying how well humans can recognize children’s gestures. We will compare human recognition rates to the rates of the automated recognition algorithms we used in our previous work. This will help us… Read More

In a previous post, we discussed our ongoing work on studying children’s gestures. We studied a corpus of children’s and adults’ gestures and analyzed 22 different articulation features, which we are pleased to announce has been accepted for publication at… Read More

One of the projects our lab has been working on has been a qualitative analysis of the children’s gesture data from our MTAGIC project. We submitted an extended abstract about this work to CHI and it was accepted! In the… Read More

In my last post I discussed some work on the $-family of recognizers. Since then, I’ve been working on designing a standalone application for running gesture recognition experiments using the $-family. The application will also allow the user to design… Read More

The $-family of recognizers are lightweight, easy to implement gesture recognizers that allow for quick development of 2-D gesture-based interfaces. These algorithms are short (less than 100 lines of code each) allowing for easy incorporation by developers into new projects.… Read More