Automatic Gait Recognition using Hybrid Neural Network
Automatic Gait Recognition using Hybrid Neural Network
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Keywords

gait recognition
VI-2DPCA
FAR
FRR

How to Cite

Drishty, & Jasmeen Gill. (2017). Automatic Gait Recognition using Hybrid Neural Network. Global Journal of Computer Science and Technology, 17(E1), 13–16. Retrieved from https://gjcst.com/index.php/gjcst/article/view/643

Abstract

Gait is a biometric trait that has been used for user authentication or verification on the basis of various attributes of gait Gait of an individual get affected due to variation in mood emotions age and weight due to these variation a perfect model is not possible that can be developed so that these all factors can be eliminated In the proposed work CASIA dataset has been used as standard dataset This dataset contains samples of 16 different individuals that have been taken at 0 45 90 degrees of angles Afterwards silhouette images have been taken for feature extraction from the gait samples using variable2-dimenssiaonl principal component analysis with neural network classifier Along with this validation of the proposed work has been done using two performance evaluation parameters namely FAR and FRR through confusion matrix
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