One shot learning gesture recognition with Kinect sensor

Di Wu, Fan Zhu, Ling Shao, Hui Zhang

Research output: Contribution to conferencePaper

4 Citations (Scopus)


Gestures are both natural and intuitive for Human-Computer-Interaction (HCI) and the one-shot learning scenario is one of the real world situations in terms of gesture recognition problems. In this demo, we present a hand gesture recognition system using the Kinect sensor, which addresses the problem of one-shot learning gesture recognition with a user-defined training and testing system. Such a system can behave like a remote control where the user can allocate a specific function using a prefered gesture by performing it only once. To adopt the gesture recognition framework, the system first automatically segments an action sequence into atomic tokens, and then adopts the Extended-Motion-History-Image (Extended-MHI) for motion feature representation. We evaluate the performance of our system quantitatively in Chalearn Gesture Challenge, and apply it to a virtual one shot learning gesture recognition system.
Original languageEnglish
Publication statusPublished - Nov 2012
EventACMMM 2012 - 20th Anniversary ACM Multimedia Conference - Nara, Japan
Duration: 1 Nov 2012 → …


ConferenceACMMM 2012 - 20th Anniversary ACM Multimedia Conference
Period1/11/12 → …


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