Vision-based Hand Gesture Spotting and Recognition

摘要：

In this paper, we propose a dynamic gesture spotting and recognition algorithm using our stereovision system. The 3D trajectories of hand gestures are First reconstructed by a stereovision-based motion capture platform. Hand gestures can then be segmented from the trajectory in real time by using proposed gesture spotting algorithm. Discrete cosine transforms coefficients, complex index and gesture entropy features are extracted to represent the gestures. With these features, one-class SVM is adopted for gesture classification. The experimental results demonstrate the feasibility of proposed spotting and recognition algorithm.

关键词： gesture recognition gesture spotting computer vision one-class SVM

作者: Can Xie Jun Cheng Qi Xie Wenchuang Zhao

作者单位: Shenzhen Institutes of Advanced Technology,Chinese Academy of Sciences,China The Chinese University of Hong Kong,Hong Kong,China

会议类型: 国际会议

会议名称: 2010 International Conference on Information,Networking and Automation(2010 IEEE信息网络与自动化国际会议 ICINA 2010)

会议地点: 昆明

会议语种:英文

页码: 391-395

在线出版日期: 2010-10-17（万方平台首次上网日期，不代表论文的发表时间）