Hand part labeling and gesture recognition from RGB-D data

被引：0
|
作者：
Yao, Yuan [1 ,2 ]
Zhang, Linjian [1 ]
Qiao, Wenbao [1 ]
机构：
[1] Rapid Manufacture Engineering Center, Shanghai University, Shanghai 200444, China
[2] Shanghai Key Laboratory of Manufacturing Automation and Robotics, Shanghai 200072, China
来源：
Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics | 2013年 / 25卷 / 12期
关键词：
Palmprint recognition;
D O I：
暂无
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
For depth sensor based hand gesture recognition, how to collect training data and built a gesture database with suitable size are challenging tasks. In this paper, we present a semi-automatic labeling scheme for establishing the real hand gesture dataset. A framework for developing hand gesture driven desktop applications is designed based on this scheme, which use RGB-D sensor as input. Moreover, a hand contour model is proposed to simplify the gesture matching process and reduce the computational complexity. The experimental evaluations and a demo application demonstrate the effectiveness of this framework.
引用
收藏
页码：1810 / 1817
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