Intelligent supervisory system based on gait recognition

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Intelligent supervisory system based on gait recognition

Received:2008-09-01 Revised:2008-10-15 Online:2009-04-22 Published:2009-02-01

基于步态识别的智能监控系统研究

王科俊刘丽丽贲晛烨

哈尔滨工程大学自动化学院哈尔滨工程大学

通讯作者: 刘丽丽

Abstract

Abstract: In view of the existing video frequency monitoring technology only relies on the human eye for the examination and lacks intelligence, this article carried out research into the supervisory system based on the gait recognition intelligence. A novel gait representation was proposed. Body silhouette extraction was achieved by background subtraction. A gait cycle was obtained by the correlated signal of the ratio of width and height of human body. Gait energy image was applied on the binary image sequence to construct the feature vector. Then PCA or (2D)2PCA was used to reduce into a low dimension space. The nearestneighbor classifier was adopted to distinguish. This gait recognition method can decrease the influence of the early preprocess effectively; moreover, it makes very good recognition progress under the three visual angles of our gait database in which the camera is put with certain angle of depression.

Key words: gait recognition, intelligence supervisory, gait energy image, principal component analysis, two dimensional principal component analysis

摘要： 针对现有的视频监控技术仅依赖人眼的检测，缺乏智能性，进行了基于步态识别的智能监控系统研究，应用背景减除法分割出人体轮廓。通过人体宽高比的相关信号确定运动周期，再对二值周期序列进行步态能量图像(GEI)合成。运用主成分分析或行列相结合的二维主成分分析((2D)2PCA)提取特征主向量，采用最近邻分类器分类。实验结果表明，该方法可以有效降低前期处理对分类识别的影响，而且在我们自己建立的摄像头摆放有一定俯角的步态数据库中3个视角下取得很好的识别效果。

关键词: 步态识别, 智能监控, 步态能量图像, 主成分分析, 二维主成分分析

王科俊 WANG Ke-Jun . Intelligent supervisory system based on gait recognition[J]. Journal of Computer Applications.

王科俊刘丽丽贲晛烨. 基于步态识别的智能监控系统研究[J]. 计算机应用.

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