Robust hand posture recognition based on RGBD images
This paper proposes a robust hand posture recognition system based on RGBD images.While much research has focused on human body posture recognition,this work investigates skeleton-free hand detection,tracking and posture recognition.This work consists of two different parts.In the first part,we utilize random forest to get pixel detection of hand and mean-shift to track hand based on RGBD images.In the second part,we implemented extraction of different features and RBF support vector machine to recognize multiple hand postures.This system has two advantages: it is skeleton-free and works in wider area; it is more robust by combining depth and color features.At last,we use the posture recognition system to control robots in virtual reality platform.
Hand posture recognition RGBD images Random forest Support vector machine
Liang Dong Hongpeng Wang Ziyi Hao Jingtai Liu
Institute of Robotics and Automatic Information System,Nankai University,Tianjin 300071;Tianjin Key Laboratory of Intelligent Robotics,Nankai University,Tianjin 300071
国际会议
长沙
英文
2735-2740
2014-05-31（万方平台首次上网日期，不代表论文的发表时间）