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Multi-View Large Population Gait Database With Human Meshes and Its Performance Evaluation
2022
IEEE Transactions on Biometrics Behavior and Identity Science
Existing model-based gait databases provide the 2D poses (i.e., joint locations) extracted by general pose estimators as the human model. However, these 2D poses suffer from information loss and are of relatively low quality. In this paper, we consider a more informative 3D human mesh model with parametric pose and shape features, and propose a multi-view training framework for accurate mesh estimation. Unlike existing methods, which estimate a mesh from a single view and suffer from the
doi:10.1109/tbiom.2022.3174559
fatcat:vo6vkigozze7hfb36bcq7iji7q