Partial silhouette-based gait recognition

Abstract

Gait analysis refers to identification of a person from the systemic study of the motions of his/her different body parts at the time of walking. It is one of the behavioural biometric approaches to human identification. Like other behavioural approaches, gait also suffers from low-repeatability leading to poor recognition accuracy. Therefore, multimodal systems are required for better recognition accuracy. With the advent of multimodal biometric systems there is a need for low-cost methods for individual biometric modalities so that the overall complexity of the system does not overshoot the real-time requirements. In view of this, a partial-silhouette-based approach for gait recognition is reported in this article. This approach is translation, rotation and scale invariant and is low-cost in terms of computational complexity. Experimental results and comparative performance analysis on benchmark dataset reveal the potential of the partial-silhouette-based approach.