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Performance Evaluation of Model-based Gait on Multi-view Very Large Population Database with Pose Sequences
IEEE Transactions on Biometrics Behavior and Identity Science
Model-based gait recognition is considered to be promising due to the robustness against some variations, such as clothing and baggage carried. Although model-based gait recognition has not been fully explored due to the difficulty of human body model fitting and the lack of a large-scale gait database, recent progress in deep learning-based approaches to human body model fitting and human pose estimation is mitigating the difficulty. In this paper, we, therefore, address the remaining issue bydoi:10.1109/tbiom.2020.3008862 fatcat:bnib4kb7zjhypi26gphodmy4bq