步态能量图的局部纹理特征分析方法

吉林大学学报(工学版) ›› 2013, Vol. 43 ›› Issue (增刊1): 193-198.

步态能量图的局部纹理特征分析方法

张元元¹, 李静², 姜树明¹, 杨子江¹, 张江州¹

1. 山东省科学院情报研究所,济南 250014;
2. 山东省工会管理干部学院信息工程学院,济南 250100

收稿日期:2012-06-05 发布日期:2013-06-01
作者简介:张元元(1984-),男,博士,助理研究员.研究方向:图像处理,模式识别与计算机视觉.E-mail:zhangyy@sdas.org
基金资助:
山东省科技发展计划项目(2012GSF12004).

Local features of gait energy image through the method of texture analysis

ZHANG Yuan-yuan¹, LI Jing², JIANG Shu-ming¹, YANG Zi-jiang¹, ZHANG Jiang-zhou¹

1. Information Research Institute, Shandong Academy of Sciences, Jinan 250014, China;
2. School of Information Engineering, Shandong Institute of Trade Unions' Administration Cadres, Jinan 250100, China

Received:2012-06-05 Published:2013-06-01

摘要/Abstract

摘要：

基于步态能量图表示方法,采用纹理特征分析方法对其亮度值的局部空间分布特性进行分析,得到局部变化幅度、局部标准差、局部熵三种纹理特征。采用经典的欧氏距离和最近邻分类器完成分类识别。CASIA步态数据库上的实验结果验证了算法的有效性。

关键词: 步态识别, 步态能量图, 灰度图像, 亮度分布, 局部纹理特征

Abstract:

Based on the representation of gait energy image (GEI),the method of texture analysis was used to describe the local space distribution of pixel brightness.Three different local textural features which are the range of local brightness (ROLB),the standard deviation of local brightness (SDOLB),and the entropy of local brightness (EOLB) were obtained.The classic Euclidean distance and nearest neighbor classifier were adopted to discriminate different patterns.The experiments on CASIA gait database demonstrate the effectiveness of the proposed method.

Key words: gait recognition, gait energy image, gray image, brightness distribution, local texture features

中图分类号:

TP391

张元元, 李静, 姜树明, 杨子江, 张江州. 步态能量图的局部纹理特征分析方法[J]. 吉林大学学报(工学版), 2013, 43(增刊1): 193-198.

ZHANG Yuan-yuan, LI Jing, JIANG Shu-ming, YANG Zi-jiang, ZHANG Jiang-zhou. Local features of gait energy image through the method of texture analysis[J]. 吉林大学学报(工学版), 2013, 43(增刊1): 193-198.

参考文献

[1] Nixon M S,Carter J N.Advances in automatic gait recognition [C]// Proc of Sixth IEEE International Conference on Automatic Face and Gesture Recognition,2004:139-144.

[2] 张元元.基于序列统计特性的步态识别算法研究.济南:山东大学,2010. Zhang Yuan-yuan.Gait recognition based on statistical characteristics of image sequences.Jinan:Shandong University,2010.

[3] Wang L,Ning H Z,Tan T T,et al.Fusion of static and dynamic body biometrics for gait recognition [J].IEEE Transactions on Circuits and Systems for Video Technology,2004,14(2):149-158.

[4] Wang L,Tan T T,Hu W M,et al.Automatic gait recognition based on statistical shape analysis [J].IEEE Transactions on Image Processing,2003,12(9):1120-1131.

[5] Zhang Y Y,Wu X J,Ruan Q Q.Combining procrustes shape analysis and shape context descriptor for silhouette-based gait recognition [J].Electronics Letters,2009,45(13):674-675.

[6] 张元元,吴晓娟,阮秋琦.基于切向角特征的统计步态识别 [J].模式识别与人工智能,2010,23(3):539-545. Zhang Yuan-yuan,Wu Xiao-juan,Ruan Qiu-qi.Statistical gait recognition based on tangent angle features[J].Pattern Recognition and Artificial Intelligence,2010,23(3):539-545.

[7] Han J,Bhanu B.Individual recognition using gait energy image [J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2006,28(2):316-322.

[8] Chen C,Liang J,Zhao H,et al.Frame difference energy image for gait recognition with incomplete silhouettes [J].Pattern Recognition Letters,2009,30(11):977-984.

[9] Lee H,Hong S,Nizami I F,et al.A noise robust gait representation:motion energy image [J].International Journal of Control,Automation and Systems,2009,7(4):638-643.

[10] Haralick R M,Shanmugam K,Dinstein I H.Textural features for image classification [J].IEEE Transactions on Systems,Man,and Cybernetics,1973,3(6):610-621.

[11] Shannon C E,Weaver W.The mathematical theory of communication[M].Urbana,IL:University of Illinois Press,1949.

[12] Yu S,Tan D,Tan T.A framework for evaluating the effect of view angle,clothing and carrying condition on gait recognition[C]//Proc 18th ICPR,2006:441-444.

[13] Cheng M H,Ho M F,Huang C L.Gait analysis for human identification through manifold learning and HMM [J].Pattern Recognition,2008,41(8):2541-2553.

[14] Lee H,Hong S,Kim E.Neural network ensemble with probabilistic fusion and its application to gait recognition [J].Neurocomputing,2009,72(7):1557-1564.

[15] 张元元,吴晓娟,阮秋琦.基于快速形状匹配的步态识别算法[C]//2009年全国模式识别学术会议暨中日韩模式识别学术研讨会,2009:558-562. Zhang Yuan-yuan,Wu Xiao-juan,Ruan Qiu-qi.Gait recognition based on fast shape matching.[C]//Proc of 2009 Chinese Conference on Pattern Recognition (CCPR2009),2009:558-562.

[16] Sarkar S,Phillips P J,Liu Z,et al.The humanid gait challenge problem:data sets,performance,and analysis [J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2005,27(2):162-177.

[17] 王科俊,贲晛烨,刘丽丽,等.基于能量的信息融合步态识别 [J].华中科技大学学报:自然科学版,2009,37(5):14-17. Wang Ke-jun,Ben Xian-ye,Liu Li-li,et al.Gait recognition using information fusion of energy [J].Journal of Huazhong University of Science and Technology (Nature Science Edition),2009,37(5):14-17.

[18] Zhang E,Ma H,Lu J,et al.Gait recognition using dynamic gait energy and PCA+LPP method [C]// Proc of International Conference on Machine Learning and Cybernetics,Baoding,China,2009:50-53.

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