View-invariant 3D hand trajectory-based recognition

被引：1
|
作者：
Zhang, Yi [1 ]
Zhang, Shuo [1 ]
Luo, Yuan [2 ]
机构：
[1] Institute of Automation, Chongqing University of Posts and Telecommunications, Shapingba, Chongqing 400065, China
[2] Institute of Optoelectronics Engineering, Chongqing University of Posts and Telecommunications, Shapingba, Chongqing 400065, China
来源：
Dianzi Keji Daxue Xuebao/Journal of the University of Electronic Science and Technology of China | 2014年 / 43卷 / 01期
关键词：
Palmprint recognition - Trajectories - Gesture recognition - Image segmentation;
D O I：
10.3969/j.issn.1001-0548.2014.01.010
中图分类号：
学科分类号：
摘要：
This paper proposes a novel method for view-invariant 3D hand trajectory-based recognition. The image depth information in gesture segmentation is collected by using Kinect sensor. View-invariant 3D hand trajectory is represented by improving centroid distance function. Hidden Markov model is applied to train and recognize hand gesture. Experiment results show that the proposed method is robust under the condition of different illumination and complex background. The illustrated system can successfully recognize spotted hand gestures with a 97.7% recognition rate for Arabic numbers 0 to 9.
引用
收藏
页码：60 / 65
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