Using a generic model for codebook-based gait recognition algorithms

Gait has emerged as a distinguishable human biological trait. It refers to the walking style of an individual and is considered an important biometric feature for person identification. Codebook based gait recognition algorithms have demonstrated excellent performance by achieving high recognition rates. However, such methods construct a codebook for each database or scenario. In this paper, we investigate the idea of using a generic codebook for gait recognition. The proposed codebook is built by using spatiotemporal characteristics of gait sequences from a large diverse synthetic gait database. We also propose a gait recognition algorithm based on this generic codebook. The advantages of the proposed algorithm over the existing methods include its independency from generating a codebook for each database, rather the proposed generic codebook can be used to encode any gait scenario. Moreover, the proposed algorithm is model free and does not require human body segmentation or modeling. The performance of the proposed generic codebook-based gait recognition algorithm is evaluated on two large gait databases TUM GAID and CMU MoBo, and recognition rate reveals the effectiveness of the proposed algorithm.