IMAGE BASED HUMAN GAIT RECOGNITION

Human gait is a valuable biometric cue that can be used for human identification besides other biometrics such as faces & fingerprints. The term gait recognition is typically used to signify the identification of people in image sequences by the way they walk. Gait is determined by the physical characteristics of each individual, and so is believed to be as unique to the person as a fingerprint is. Human identification using gait is a challenging computer vision task. Gait is also one of the few biometrics that can be measured at a distance, which makes it useful in surveillance applications as well. In this paper, our objective is to develop robust methods for extracting discriminate gait features automatically and passively from low-resolution video. For this, we explore gait recognition technique of a non-parametric approach that derives its classification feature from the image self-similarity plot of a walking sequence.