期刊
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
卷 23, 期 8, 页码 1237-1246出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.engappai.2010.07.004
关键词
Human recognition; Biometrics; Gait; Model based; Bilateral symmetry
We have presented a model-based approach for human gait recognition which is based on analyzing the leg and arm movements An initial model is created based on anatomical proportions and a posterior model is constructed upon the movements of the articulated parts of the body using active contour models and the Hough transform Fourier analysis is used to describe the motion patterns of the moving parts The k-nearest neighbor rule applied to the phase-weighted Fourier magnitude of each segment s spectrum is used for classification In contrast to the existing approaches the main focus of this paper is on increasing the discrimination capability of the model through extra features produced from the motion of the arms Experimental results indicate good performance of the proposed method The technique has also proved to be able to reduce the adverse effects of self-occlusion which is a common incident in human walking (C) 2010 Elsevier Ltd All rights reserved
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据