Human Gait Recognition for Different Viewing Angles using PCA
نویسندگان
چکیده
Human gait recognition is a developing biometric engineering now a days. It perceives the individual from its walk and above all from a distance without subject’s cooperation. As human gait recognition system is influenced by diverse view variations effects. So, in this paper we have proposed a human gait recognition strategy for the images caught from distinctive viewing edges (0, 45, 90 degree). There are two phases in this proposed work: feature extraction and recognition. Principal Component Analysis is used for feature extraction and for similitude estimation Euclidean distance is used. Experiments are performed on CASIA A gait dataset. Keywords— Euclidean Distance, Human Gait, Principal Component Analysis (PCA).
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