Silhouette Analysis Based Gait Recognition for Human Identification

In this research, gait recognition as technique of recognizing a people based on how they walk has been studied. The fact that this technique does not need any interaction or cooperation from the object make it an attractive method for identifying people. Locomotion human model has been developed by extracting gait features or properties from a sequence of images. The developed model reduces the external noisy factors, for example, shoes, clothing, hand bags, and environmental context. Moreover, an advanced machine learning algorithm, from computer vision library OpenCV, has been utilized for gait recognition to give nearly real time recognition system. finally, the reliability of the proposed gait recognition system was 89.7% with ability to detect person 40 meters away from the camera.