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

页码：1810 / 1817

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