A model-based gait recognition method with body pose and human prior knowledge
作者：
Highlights：
• We propose a novel model-based gait recognition method, PoseGait, which exploits human pose as feature. The method can achieve high recognition rate despite the low dimensional feature (only 14 body joints).
• We design dedicated features based on 3D pose information. We demonstrate experimentally the advantage of these features.
• CNN nor RNN/LSTM can successfully extract spatio-temporal gait feature with the help of fusing two losses.
摘要
•We propose a novel model-based gait recognition method, PoseGait, which exploits human pose as feature. The method can achieve high recognition rate despite the low dimensional feature (only 14 body joints).•We design dedicated features based on 3D pose information. We demonstrate experimentally the advantage of these features.•CNN nor RNN/LSTM can successfully extract spatio-temporal gait feature with the help of fusing two losses.
论文关键词：Gait recognition,Human body pose,Spatio-temporal feature,
论文评审过程：Received 27 April 2019, Revised 7 August 2019, Accepted 26 September 2019, Available online 30 September 2019, Version of Record 4 October 2019.
论文官网地址：https://doi.org/10.1016/j.patcog.2019.107069
