Research on hand gesture recognition based on inner-distance shape context and bag of words model

被引：0

作者：

Zhang, Qiuyu ^{[1
]}

Wei, Huiyi ^{[1
]}

Xu, Zhigang ^{[1
]}

Zhang, Moyi ^{[1
]}

Duan, Hongxiang ^{[1
]}

Lv, Lu ^{[1
]}

机构：

[1] School of Computer and Communication, Lanzhou University of Technology

来源：

Journal of Information and Computational Science | 2014年 / 11卷 / 09期

关键词：

Bag of words model; Deformable hand gesture; Hand gesture recognition; Inner-distance shape context; Shape context descriptors;

D O I：

10.12733/jics20103703

中图分类号：

学科分类号：

摘要：

A method of gesture recognition based on inner-distance shape context and bag of words (Inner-distance Shape Context-Bag of Words, IDSC-BOW) is proposed in this paper, mainly aimed at the influence on the accuracy of recognition in representing process of gestures caused by joints or part structures deformations. Firstly, the method uses elliptical skin model to segment, get the binary gesture area and extract contours. Then, sample points on the contour are obtained by uniform sampling. The visual dictionary is generated through K-means clustering with inner-distance shape context features of hands. The generated visual dictionary is used to map the inner-distance shape context features of gestures into a collection of visual words. The BOW vectors are obtained by process of frequency statistic and normalization on the visual words. Finally, the Support Vector Machine (SVM) classifier is used for classification. The experimental results show that the method has higher recognition rate on ten kinds of hand gestures as 0-9. It keeps good robustness on joints of hands and part structures deformations. Copyright © 2014 Binary Information Press.

引用

页码：2895 / 2904

页数：9

共 18 条

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