Kernel based hand gesture recognition using kinect sensor

Category 4. A machine learning based methodology is proposed to recognize a predefined set of hand gestures using depth images. For such purpose, a RGBD sensor (Microsoft kinect) is employed to track the hand position. Thus, a preprocessing stage is presented to subtract the region of interest from depth images. Moreover, a learning algorithm based on kernel methods is used to discover the relationships among samples, properly describing the studied gestures. Proposed methodology aims to obtain a representation space which allow us to identify the dynamic of hand movements. Attained results show how our approach presents a suitable performance for detecting different hand gestures. As future work, we are interested in recognize more complex human activities, in order to support the development of human-computer interface systems.