Gait recognition based on row mass vector of frame difference energy image

doi:10.11772/j.issn.1001-9081.2014.05.1364

Journal of Computer Applications ›› 2014, Vol. 34 ›› Issue (5): 1364-1368.DOI: 10.11772/j.issn.1001-9081.2014.05.1364

• Artificial intelligence • Previous Articles Next Articles

Gait recognition based on row mass vector of frame difference energy image

LI Rui,CHEN Yong,YU Lei

College of Computer and Information Science, Chongqing Normal University, Chongqing 401331, China

Received:2013-11-14 Revised:2013-12-12 Online:2014-05-30 Published:2014-05-01
Contact: CHEN Yong
Supported by:
National Natural Science Foundation;The Science and Technology Project Affiliated to the Education Department of Chongqing

基于帧差能量图行质量向量的步态识别算法

李锐,陈勇,余磊

重庆师范大学计算机与信息科学学院，重庆 401331

通讯作者: 陈勇
作者简介:李锐(1984-),女,河南泌阳人,硕士研究生,主要研究方向：数字图像处理；陈勇(1971-)，男，重庆巴南人，副教授，博士，主要研究方向：信息安全、数字图像处理、智能计算；余磊(1980-)，男，湖南岳阳人，副教授，博士，主要研究方向：模式识别、图像处理、机器学习。
基金资助:
国家自然科学基金资助项目;重庆市教委基金资助项目;重庆市教委科技项目

Abstract

Abstract:

To effectively capture the dynamic information of the gait and accelerate the authentication and identification, a novel gait recognition algorithm was presented in this paper, which employed the row mass vector of the Frame Difference Energy Image (FDEI) as the gait features. The gait contour images were extracted through the object detection, binarization, morphological process and connectivity analysis of the original images. Using the width of the contour images sequence, the quasi-periodicity analysis and the row mass vector of the frame difference image were obtained, then the Continuous Hidden Markov Model (CHMM) was employed to train and recognize the parameters of model. The proposed algorithm was applied to Central Asia Student International Academic (CASIA) gait database. The experimental results show that it can easily extract the features of the gait with low dimension, achieving fast recognition speed and high recognition rate, so it can be used for real-time gait recognition.

摘要：

为了有效地捕捉步态的连续性动态信息，快速进行身份认证和识别，提出一种以帧差能量图（FDEI）的行质量向量作为步态特征的步态识别方法。该算法通过目标检测、二值化、形态学处理、连通性分析等预处理后得到步态轮廓图像，并利用其序列的宽度进行准周期性分析，再用连续隐马尔可夫模型(CHMM)对所提取的步态帧差能量图行质量向量进行模型参数训练和识别。在CASIA数据库上进行了仿真实验，结果表明该算法具有特征提取简单、特征维数低、识别速度快和识别率高的优点，可以满足实时识别的需要。

CLC Number:

TP391

LI Rui CHEN Yong YU Lei. Gait recognition based on row mass vector of frame difference energy image[J]. Journal of Computer Applications, 2014, 34(5): 1364-1368.

李锐陈勇余磊. 基于帧差能量图行质量向量的步态识别算法[J]. 计算机应用, 2014, 34(5): 1364-1368.

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Gait recognition based on row mass vector of frame difference energy image

基于帧差能量图行质量向量的步态识别算法

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