A survey on gait recognition against occlusion: taxonomy, dataset and methodology

Traditional biometric techniques often require direct subject participation, limiting application in various situations. In contrast, gait recognition allows for human identification <i>via</i> computer analysis of walking patterns without subject cooperation. However, occlusion remains a key challenge limiting real-world application. Recent surveys have evaluated advances in gait recognition, but only few have focused specifically on addressing occlusion conditions. In this article, we introduces a taxonomy that systematically classifies real-world occlusion, datasets, and methodologies in the field of occluded gait recognition. By employing this proposed taxonomy as a guide, we conducted an extensive survey encompassing datasets featuring occlusion and explored various methods employed to conquer challenges in occluded gait recognition. Additionally, we provide a list of future research directions, which can serve as a stepping stone for researchers dedicated to advancing the application of gait recognition in real-world scenarios.