[1]吴彩芳[],谢钧[],俞璐[]. 基于骨骼和深度信息的手势识别的研究与应用[J].计算机技术与发展,2016,26(08):200-204.
　WU Cai-fang[],XIE Jun[],YU Lu[]. Research and Application of Gesture Recognition Based on Information of Body Skeleton and Depth[J].,2016,26(08):200-204.
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 基于骨骼和深度信息的手势识别的研究与应用()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
26
期数:
2016年08期
页码:
200-204
栏目:
应用开发研究
出版日期:
2016-08-10

文章信息/Info

Title:
 Research and Application of Gesture Recognition Based on Information of Body Skeleton and Depth
文章编号:
1673-629X（2016)08-0200-05
作者:
 吴彩芳[1]; 谢钧[1]; 俞璐[2]
 1.解放军理工大学 指挥信息系统学院；2.解放军理工大学 通信工程学院
Author(s):
 WU Cai-fang[1]; XIE Jun[1]; YU Lu[2]
关键词:
 ; 静态手势识别; 手势交互系统; Hu矩; 支持向量机
Keywords:
 ; static gesture recognition; gesture interactive system; Hu’s moment; support vector machine
分类号:
TP391.4
文献标志码:
A
摘要:
 文中研究了基于Kinect的手势识别技术，设计并实现了一个功能完善、性能优越的小型手势交互系统。首先结合Kinect获取的人体骨骼信息和深度信息，实现了手部的追踪和提取，并且实验效果不受实验背景、光线、实验者的肤色和服装的影响。然后根据初步获取的手型二值图噪声分布特点，提出一种过滤小规模连通分量像素点的方法对二值图进行去噪。最后，分别以手型二值图Hu矩和手型轮廓二值图Hu矩为特征，使用SVM分类器进行训练和识别。实验结果表明，同手型二值图的Hu矩相比，以手型轮廓二值图的Hu矩作为特征具有明显优势。
Abstract:
 It explores the technology of gesture recognition based on Kinect in this paper,and designs and implements a small gesture in-teractive system with perfect function and excellent performance. At first,the Skeleton Information and Depth Information from Kinect is used to track and extract hand from the background. The result doesn’ t be affected by the background,light,and experimenter’ s skin col-or and costume. Then,according to the distribution of noise from preliminary acquisition in the binary images,a method of filtering the small scale connected component pixels is put forward to denoise. At last,Hu’ s moments of hand binary images and hand contour binary images are used as features to train the Support Vector Machine ( SVM) classifiers respectively. The experimental results show that com-pared with Hu’ s moments of hand binary images,the Hu’ s moments of the hand contour binary images have obvious advantages.

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更新日期/Last Update: 2016-09-29