Human Identification using MDA,LDA,BPNN,NN Techniques

Namita Kakkar, Neha Mehan, Robindeep Kaur


Gait recognition is one kind of biometric technology that can be used to monitor people without their cooperation. Controlled environments such as banks, military installations and even airports need to be able to quickly detect threats and provide 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 an individual by the manner in which they walk. Gait is less unobtrusive biometric, which offers the possibility to identify people at a distance, without any interaction or co-operation from the subject; this is the property which makes it so attractive. This paper proposed new method for gait recognition. . In this thesis I will present the review of gait recognition system, different approaches and classification categories of Gait recognition like model free and model based approach, MDA, ENN, NN.


Keywords: Multiple Descriminant Analysis (MDA), Neural Network (NN), Linear Descriminant Analysis(LDA),Back Propagation Neural Network(BPNN),Feature Extraction, Background Subtraction.

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