Abstract:

Existing gait recognition methods fail to make full use of frame-level feature information and spatio-temporal feature information. To solve this issue, a novel frame-temporal gait network based on frame-spatio-temporal double branch network is proposed, which includes two branches, the one is frame-level feature extraction, and another is spatial-temporal feature extraction. Then, a temporal integration module is proposed to bridge two branches, which enables the information of frame-level feature extraction branch to be integrated with the spatial-temporal feature extraction branch many times and enhances the capability of feature representation. The proposed gait recognition network experiments on popular gait recognition datasets CASIA-B and OU-MVLP. The results of experiments verify the effectiveness of the proposed method under normal walking and complex conditions.

Key words: Gait recognition, double branch, temporal integration