吉林大学学报(工学版) ›› 2015, Vol. 45 ›› Issue (5): 1608-1614.doi: 10.13229/j.cnki.jdxbgxb201505033

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基于相关性度量的触觉步态特征优化

张艳1, 2, 梁栋3, 鲍文霞3, 朱明1, 3, 孙怡宁4   

  1. 1.安徽大学 计算智能与信号处理教育部重点实验室,合肥 230039;
    2.安徽大学 物理与材料科学学院,合肥 230601;
    3.安徽大学 电子信息工程学院,合肥 230601;
    4.中国科学研究院智能机械研究所,合肥 230031
  • 收稿日期:2013-10-09 出版日期:2015-09-01 发布日期:2015-09-01
  • 通讯作者: 梁栋(1963-),男,教授,博士生导师.研究方向:模式识别,图像处理.E-mail:dliang@ahu.edu.cn
  • 作者简介:张艳(1982-）,女,博士研究生.研究方向:图像处理,步态识别.E-mail:zhangyan@ahu.edu.cn
  • 基金资助:
    国家自然科学基金项目(61172127,61201127); 高等学校博士学科点专项科研基金项目(20113401110006); 安徽大学青年科学研究基金项目(KJQN1107)

The haptic force feature optimization based criterion of correlation

ZHANG Yan1, 2, LIANG Dong3, BAO Wen-xia3, ZHU Ming1, 3, SUN Yi-ning4   

  1. 1.Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, Anhui University, Hefei 230039,China;
    2.School of Physics and Materials Science, Anhui University, Hefei 230601,China;
    3.School of Electronics and Information Engineering, Anhui University, Hefei 230601,China;
    4.Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031,China
  • Received:2013-10-09 Online:2015-09-01 Published:2015-09-01

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摘要： 在现有动力学特征基础上,提出了基于相关性度量的触觉步态组合特征优化方法(CCFO)。采用数学形态学提取触觉步态区域特征,同时提取触觉步态的图像特征,包括校正后外接矩形长宽比和对比度、相关性、熵等特征;采用相关性度量准则优化得到动力学特征,通过分析图像特征的相关性保留最优图像特征,优化后特征线性叠加构成触觉步态特征集。实验数据采用ITCSH GaitⅡ步态数据库,计算各特征组内相关系数和变异系数,结果表明,各特征具有较好的稳定性,并在身份识别中验证了特征集的有效性,实验结果说明CCFO方法可以有效地减少特征数,提高识别率。

关键词: 计算机应用, 区域特征, 外接矩形长宽比, 纹理特征, 相关性度量

Abstract: Based on the haptic force dynamics feature, a method of Correlation-basis Combination Feature Optimization (CCFO) is proposed. First, the regional features of haptic force are extracted using mathematical morphology. Meanwhile, image features are extracted, such as the improved ratio of length to width, the contrast, the correlation, and the entropy. Then, the haptic force dynamics feature is optimized by criterion of correlation, and the optimal haptic force image feature is kept through analyzing the correlation coefficient. Finally, the haptic force feature set is obtained by linear summation. The experimental data are taken from the ITCSH Gait II database. The stability of the features is studied by calculating the intraclass correlation coefficient and coefficient of variation. The results show that the CCFO method can effectively reduce the number of features and hence improve the recognition rate in identity recognition.

Key words: computer application, region feature, ratio of length to width, textural feature, criterion of correlation

中图分类号: 

  • TP391.4
[1] Xu S, Zhou X, Sun Y. A genetic algorithm-based feature selection method for human identification based on ground reaction force[C]∥Proc the 1st ACM/SIGEVO Summit on Genetic and Evolutionary Computation, Shanghai, 2009:665-670.
[2] Lemaire Edward D, Biswas Ajoy, Kofman Jonathan. Plantar pressure parameters for dynamic gait stability analysis[C]∥Proc Annual International Conference of the IEEE on Engineering in Medicine and Biology Society, New York, 2006:4465-4468.
[3] Surdilovic D, Jinyu Z, Bernhardt R. Gait phase and centre of pressure measuring system[C]∥Proc International Conference of the IEEE on Industrial Informatics, Germany, Berlin, 2004:331-334.
[4] Kerstin Bosch, Joachim Gerss, Dieter Rosenbaum. Preliminary normative values for foot loading parameters of the developing child[J]. Gait & Posture, 2007, 26(2): 238-247.
[5] 姚志明. 基于步态触觉信息的身份识别研究[D]. 合肥:中国科学技术大学信息科学技术学院,2010. Yao Zhi-ming. Gait recognition based on haptic force information[D]. Hefei:School of Information Science and Technology , University of Science and Technology of China, 2010.
[6] Gurney J K,Kersting U G,Rosenbaum D. Between-day reliability of repeated plantar pressure distribution measurements in a normal population[J]. Gait & Posture, 2008, 27(4):706-709.
[7] Yan Song-hua,Zhang Kuan,Tan Gou-qing, et al. Effects of obesity on dynamic plantar pressure distribution in Chinese prepubescent children during walking[J]. Gait & Posture, 2013, 37(1): 37-42.
[8] Rafael C G, Richard E W.Digital Image Processing[M].3rd ed. Beijing:Publishing House of Electromcs Industry, 2010: 801-861.
[9] 刘丽,匡纲要. 图像纹理特征提取方法综述[J]. 中国图象图形学报, 2009, 14(4): 622-635. Liu Li, Kuang Gang-yao. Overview of image textural feature extraction methods[J]. Journal of Image and Graphics, 2009, 14(4): 622-635.
[10] 薄华,马缚龙,焦李成. 图像纹理的灰度共生矩阵计算问题的分析[J]. 电子学报,2006, 34(1): 155-158. Bo Hua, Ma Fu-long, Jiao Li-cheng . Research on computation of GLGM of image texture[J]. Chinese Journal of Electronics,2006, 34(1): 155-158.
[11] Bartko J. The intraclass correlation coefficient as a measure of reliability[J]. Psychological Reports, 1966, 19(1): 3-11.
[12] Bilney B, Morris M, Webster K. Concurrent related validity of the GAITRite(R) walkway system for quantification of the spatial and temporal parameters of gait[J]. Gait & Posture, 2003, 17(1): 68-74.
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