Vision based dynamic hand gesture recognition for human computer interaction
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With the increased interest in human-computer interaction (HCI), there has been rapid growth of research related to gesture recognition in recent years. Hand gesture recognition from visual images forms an important part of this research. This thesis reports on our research on recognition of dynamic hand gestures having different spatio-temporal characteristics. We develop methods to recognize dynamic hand gestures with (1) local hand motion only where only the fingers and the palm move without any movement of the whole hand, (2) global motion only where the hand as a whole move in space to make different gestures, and (3) both local and global motions where the fingers and palm create different hand poses as the arm traverses along a trajectory in space. We use the concept of object-based video abstraction for segmenting the frames into video object planes (VOPs) with each VOP corresponding to one semantically meaningful hand pose or position in space. A gesture is represented as a sequence of key video object planes (key VOPs) that correspond to significantly different VOPs in the vide sequence.
Supervisors: Debashis Ghosh and Prabin Kumar Bora
ELECTRONICS AND ELECTRICAL ENGINEERING