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Abstract

Gait Recognition is one kind of biometric hi tech that can be used to monitor people without their cooperation. A specific manner or way of moving on foot is known as gait and gait recognition is the process of identifying an individual by the manner in which they walk. Gait is less undesirably noticeable biometric, which offers the possibility to locate or differentiate people at a distance, without any interaction or co-operation from the subject. This paper proposed new technique for gait recognition. In this method, frames are created from video and stored. Secondly, feature from each frame is extracted using Hanavan’s model. Here height of person, distance between two hands and distance between two legs are taken as key feature. At last K-NN with SURF and SVM are used for training and testing purpose. Here all the research work is done on gait database created using mat file. Different groups of training and testing dataset give different results.

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Keywords

Gait, SURF, SVM, K-NN.