Hybrid Classifier for gait recognition

Volume: 4    Issue: 2

Year of Publication: 2017

Pages: (20-25)

Authors: Harsimran Kaur, Er.Maninder Sharma

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Abstract

Gait recognition is one form of biometric technology that can be used to monitor people exclusive of their cooperation. Controlled environments such as banks, military installations and even airports require being able to quickly spot threats and providing differing levels of access to different user groups. Gait shows a particular way or manner of moving on foot and gait recognition is the process of identifying person by the style in which they move.. Gait is less unobtrusive biometric, which offers the possibility to identify people at a distance, without any dealings or help from the subject; this is the property which makes it so attractive. This paper proposed new method for gait recognition. In this method, firstly binary silhouette of a moving person is spotted from all frame. Secondly, feature from each frame is extracted using image processing operation. Here center of mass, step size length, and cycle length are taking as key feature. At last neural network is used for training and testing purpose. We have created different model of neural network based on hidden layer, selection of training algorithm and setting the different parameter for training. Here all research is done on gait database. Different groups of training and testing dataset give different results.

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Keywords

Gait, SURF, SVM, K-NN.