基于Trace变换的步态识别算法

吉林大学学报(工学版) ›› 2012, Vol. 42 ›› Issue (01): 156-160.

基于Trace变换的步态识别算法

贲晛烨¹, 徐森², 王科俊³

1. 山东大学信息科学与工程学院,济南 250100;
2. 盐城工学院信息工程学院,江苏盐城 224000;
3. 哈尔滨工程大学自动化学院,哈尔滨 150001

收稿日期:2010-09-19 出版日期:2012-01-01 发布日期:2012-01-01
作者简介:贲晛烨(1983-),女,讲师.研究方向:模式识别,度量学习,超分辨率人脸识别,步态识别. E-mail:benxianyeye@163.com
基金资助:
国家自然科学基金项目(60975042, 61105057);中国博士后科学基金项目(20110491087);盐城工学院人才引进专项基金项目(XKR2011019).

Gait recognition based on Trace transform

BEN Xian-ye¹, XU Sen², WANG Ke-jun³

1. School of Information Science and Engineering, Shandong University, Ji'nan 250100, China;
2. School of Information Engineering, Yancheng Institute of Technology, Yancheng 224000, China;
3. College of Automation, Harbin Engineering University, Harbin 150001, China

Received:2010-09-19 Online:2012-01-01 Published:2012-01-01

摘要/Abstract

摘要：

提出了基于Hu矩的步态周期检测算法,该算法具有尺度、平移不变性,在预处理的标准中心化之前进行,缩短了步态识别前期处理工作的时间,为实时的步态识别提供可能。在分析步态的投影特征具有身份判别的能力之后,进而引出并说明使用Trace变换特征对步态表达的想法是合理的。提出基于Trace变换的步态识别算法,详细地讨论了三种Trace变换的泛函形式,在CASIA(B)步态库上进行验证实验,最佳识别率可达84.14%。这种方法避免了动态时间规整以及线性时间归一等算法的复杂的调整过程。

关键词: 计算机应用, 步态识别, Hu矩, Radon变换, Trace变换

Abstract:

A novel gait period detection algorithm based on Hu moments was proposed. With the scaling and shift invariance attributes, this method can potentially be used preceding the standardized and centralized image processing. Therefore, the pre-processing time in gait recognition is reduced significantly, which results in the possibility of real-time gait recognition. After analysis of the ability of the projection features of the gait to distinguish identity, it was elicited that it is reasonable of using Trace transform to describe the characteristics of the gait. Following that, gait recognition based on Trace transform was proposed. Three different kinds of functional forms in Trace transform were discussed in detail and experiments were conducted on CASIA-B gait database for validation. The best recognition rate achieved was 84.14%. This method avoids the complicated rectification process of the dynamic time warping algorithm and linear time normalization algorithm.

Key words: computer application, gait recognition, Hu moments, Radon transform, Trace transform

中图分类号:

TP391.41

贲晛烨, 徐森, 王科俊. 基于Trace变换的步态识别算法[J]. 吉林大学学报(工学版), 2012, 42(01): 156-160.

BEN Xian-ye, XU Sen, WANG Ke-jun. Gait recognition based on Trace transform[J]. 吉林大学学报(工学版), 2012, 42(01): 156-160.

参考文献

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[J]. CAAI Transactions on Intelligent Systems,2011,6(1): 63-67.

[2] Boulgouris N V, Plataniotis K N, Hatzinakos D. Gait recognition using dynamic time warping//Proc of IEEE Int Symp Multimedia Signal Processing, 2004: 263-266.

[3] Boulgouris N V, Plataniotis K N, Hatzinakos D. Gait recognition using linear time normalization
[J]. Pattern Recognition,2006,39(5): 969-979.

[4] 王科俊,贲晛烨. 基于线性插值的特征模板构造的步态识别算法框架
[J]. 南京理工大学学报,2009,33(Sup.1): 215-219. Wang Ke-jun, Ben Xian-ye. Framework for gait recognition based on feature template construction using linear interpolation
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[5] Hu M K.Visual pattern recognition by moment invariant
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[7] Yu Shi-qi, Tan Dao-liang, Tan Tie-niu. A framework for evaluating the effect of view angle, clothing and carrying condition on gait recognition//Proc of the 18th International Conference on Pattern Recognition, Hong Kong, China, 2006:441-444.

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[9] Yu Shi-qi, Tan Dao-liang, Huang Kai-qi, et al. Reducing the effect of noise on human contour in gait recognition//Proc of the 2nd International Conference on Biometrics, Seoul, Korea, 2007: 338-346.

[10] Yu Shi-qi, Wang Liang, Huang Kai-qi, et al. Gait analysis for human identification in frequency domain//Proc of the 3rd International Conference on Image and Graphics, 2004: 282-285.

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