2D Motion Detection Bounded Hand 3D Trajectory Tracking and Gesture Recognition under Complex Background

Author Info

Shuangqing Wu, Zhejiang University
Yin Zhang, Zhejiang University
Sanyuan Zhang, Zhejiang University
Xiuzi Ye, Zhejiang University
Yiyu Cai, Nanyang Technological University, Singapore
Jianmin Zheng, Nanyang Technological University, Singapore
Soumita Ghosh, Nanyang Technological University, Singapore
Wenyu Chen, Nanyang Technological University, Singapore
Jane Zhang, California Polytechnic State University - San Luis ObispoFollow

Recommended Citation

Preprinted version. Published in ACM SIGGRAPH International Conference on Virtual-Reality Continuum and Its Applications in Industry Proceedings: Seoul, South Korea, December 12, 2010, pages 311-318.

Abstract

In this paper, a 2D motion detection bounded hand 3D trajectory tracking and gesture recognition system is proposed for virtual reality interactions. First, the Bayes decision rule for classification of background and foreground is utilized to automatically locate the hand that bounded within a rectangle, and then the trajectory of the hand in 3D space is tracked by mean shift particle filter and stereo imaging. The skin color feature is exploited for image matting that effectively segment the hand contour in video sequence automatically. Finally the hand gesture is recognized by the connected component analysis and line approximation.

Disciplines

Electrical and Computer Engineering

Copyright

2010 Association for Computing Machinery.

Publisher statement

This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in The 7th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and Its Applications in Industry Proceedings: Seoul, South Korea, December 12, 2010.