文档介绍：
Gait Correlation Analysis Based Human Identification#
Chen Jinyan*
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(School puter Software Tianjin University,Tianjin 300072,China
(School puter Software Tianjin University)
Abstract: Human gait identification aims to identify people by a sequence of walking images.
Comparing with fingerprint or iris based identification the most important advantage of gait
identification is that it can be done in a distance. In this paper silhouette correlation analysis based
human identification approach is proposed. By background subtracting algorithm the moving silhouette
figure can be extracted from the walking images sequence. Every pixel in the silhouette has three
dimensions: horizontal axis(x), vertical axis(y) and temporal axis(t). By moving every pixel in the
silhouette image along these three dimensions we can get a new silhouette. The correlation result
between the original silhouette and the new one can be used as the raw feature of human gait. Discrete
Fourier transform is used to extract features from this correlation result. Then these features are
normalized to minimize the affection of noise. ponent analysis method is used to reduce
the features’ dimensions. Experiment based on CASIA database shows this method has an encouraging
recognition performance.
Key words: image processing; human gait identification; image correlation; ponent
analysis
0 Introduction
Biometrics is a technology that makes use of the physiological or behavioral characteristics to
authenticate or identify people [1]. The monly used biometrics applications are fingerprint
and iris based identification.
Human gait was firstly studied in medical field [2-5]. Doctors analyzed human gait to find out
whether patients had health problem. Later researchers [5] found that just like fingerprint and iris,
almost everyone had his distinctive walking style. So someone believed that gait could also be used as
a biological feature to identify person. Co