Hand Posture Recognition and Tracking Based on Bag-of-Words forHuman Robot Interaction

摘要：

Hand posture is a natural and effective interaction between human and robot. In this paper, we use monocular camera as input device, and an improved Bag-of-Words (BoW) method is proposed to detect and recognize hand posture based on a new descriptor ARPD (Appearance and Relative Position Descriptor) and spectral embedding clustering algorithm. To track hand motion rapidly and accurately, we have designed a new framework based on improved BoW and CAMSHIFT algorithm. The thorough evaluation of our algorithm is presented to show its usefulness.

作者: Yuelong Chuang Ling Chen Gangqiang Zhao Gencai Chen

作者单位: College of Computer Science,Zhejiang University,P.R. China School of Electrical & Electronic Engineering,Nanyang Technological University,Singapore

会议类型: 国际会议

会议名称: 2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)

会议地点: 上海

会议语种:英文

页码: 538-543

在线出版日期: 2011-05-09（万方平台首次上网日期，不代表论文的发表时间）