Gait Recogniton System for Human Identification using BPNN Classifier
Oshin Sharma1, Sushil Kumar Bansal2

1Oshin Sharma, Department of Computer Science, Chitkara University, Baddi (Himachal Pradesh), India.
2Sushil Kumar Bansal, Department of Computer Science, Chitkara University, Baddi (Himachal Pradesh), India.
Manuscript received on 11 June 2013 | Revised Manuscript received on 17 June 2013 | Manuscript Published on 30 June 2013 | PP: 217-220 | Volume-3 Issue-1, June 2013 | Retrieval Number: A0913063113/13©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (

Abstract: Recognition of any individual is a task to identify people. Human recognition methods such as face, fingerprints, and iris generally require user’s cooperation, physical contact or close proximity. These methods are not able to recognize an individual at a distance therefore recognition using gait is relatively new biometric technique without these disadvantages. Human identification using Gait is method to identify an individual by the way he walk or manner of moving on foot. Gait offers ability of distance recognition or at low resolution. In this paper, firstly binary silhouette of a walking person is detected from each frame. Secondly, feature from each frame is extracted using image processing operation. Here center of mass, step size length, and cycle length are talking as key feature. At last BPNN technique is used for training and testing purpose. Here all experiments are done on gait database and input video.
Keywords: Backpropagation Neural Network (BPNN), Gait Recognition, Silhouette Images, Background Subtraction, Features Extraction.

Scope of the Article: System Integration