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 get an idea of how well humans are able to recognize children’s gestures. That way, we will have a good target accuracy for our future work on improving automated recognition of children’s gestures. Our future work will focus on improving the accuracy of recognizers for children’s gestures using the human recognition rate as the goal.

I am a rising 4th year Ph.D. student. Working on this project has helped me to better understand the ways that humans perceive gestures, which has led to some interesting discoveries on what kinds of gestures humans confuse. I look forward to applying this information to automated algorithms to improve recognition. Working on this project, I also learned how to use tools like Qualtrics and Amazon Mechanical Turk.