Sanjeev Sharma

Work place: Dept. of Computer Science, ABV- Indian Institute of Information Technology and management, Gwalior, India

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Research Interests: Artificial Intelligence, Autonomic Computing, Computing Platform, Mathematics of Computing

Biography

Sanjeev Sharma is doing his Ph.D from ABV- Indian Institute of Information Technology and management Gwalior. He did his M. Tech. from ABV- Indian Institute of Information Technology and management Gwalior, India. He received the M. Sc. degree in computer science from jiwaji university Gwalior. His area of research are soft computing, Biometrics, Artificial Intelligence.

Author Articles
Gender Identification in Human Gait Using Neural Network

By Richa Shukla Reenu Shukla Anupam Shukla Sanjeev Sharma Nirupama Tiwari

DOI: https://doi.org/10.5815/ijmecs.2012.11.07, Pub. Date: 8 Nov. 2012

Biometrics is an advanced way of person recognition as it establishes more direct and explicit link with humans than passwords, since biometrics use measurable physiological and behavioural features of a person. In this paper gender recognition from human gait in image sequence have been successfully investigated. Silhouette of 15 males and 15 females from the database collected from CASIR site have been extracted. The computer vision based gender classification is then carried out on the basis of standard deviation, centre of mass and height from head to toe using Feed Forward Back Propagation Network with TRAINLM as training functions, LEARNGD as adaptation learning function and MSEREG as performance function. Experimental results demonstrate that the present gender recognition system achieve recognition performance of 93.4%, 94.6%, and 94.7% with 2 layers/20 neurons, 3 layers/30 neurons and 4 layers/30 neurons respectively. When the performance function is replaced with SSE the recognition performance is increased by 2%, 2.4% and 3% respectively for 2 layers/20 neurons, 3 layers/30 neurons and 4 layers/30 neurons.The above study indicates that Gait based gender recognition is one of the best reliable biometric technology that can be used to monitor people without their cooperation. Controlled environments such as banks, military installations and even airports need to quickly detect threats and provide differing levels of access to different user groups.

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