LAUSR

Gait is an important biometric trait for identifying individuals. The use of inputs from multiple or moving cameras offers a promising extension of gait recognition methods. Personal authentication systems at building entrances, for example, can utilize multiple cameras installed at appropriate positions to increase their authentication accuracy. In such cases, it is important to identify effective camera positions to maximize gait recognition performance, but it is not yet clear how different viewpoints affect recognition performance. This study determines the relationship between viewpoint and gait recognition performance to construct standards for selecting an appropriate view for gait recognition using multiple or moving cameras. We evaluate the gait features generated from 3D pedestrian shapes to visualize the directional characteristics of recognition performance.