Combined Regularized Discriminant Analysis and Swarm Intelligence Techniques for Gait Recognition

• Main Authors: Tomasz Krzeszowski, Krzysztof Wiktorowicz
• Format: Article
• Language: English
• Published: MDPI AG 2020-11-01
• Series: Sensors
• Subjects: gait recognition; biometrics; regularized discriminant analysis; particle swarm optimization; grey wolf optimization; whale optimization algorithm
• Online Access: https://www.mdpi.com/1424-8220/20/23/6794

In the gait recognition problem, most studies are devoted to developing gait descriptors rather than introducing new classification methods. This paper proposes hybrid methods that combine regularized discriminant analysis (RDA) and swarm intelligence techniques for gait recognition. The purpose of this study is to develop strategies that will achieve better gait recognition results than those achieved by classical classification methods. In our approach, particle swarm optimization (PSO), grey wolf optimization (GWO), and whale optimization algorithm (WOA) are used. These techniques tune the observation weights and hyperparameters of the RDA method to minimize the objective function. The experiments conducted on the GPJATK dataset proved the validity of the proposed concept.