A 3D 2-Subiteration Thinning Algorithm for Human Pose Estimation

Markerless human body model reconstruction has been a hot research topic for decades, and it has many applications in human computer interaction (HCI), medical rehabilitation, sport training, and virtual human synthesis for games, cartoons and digital films. This paper presents a markerless 3D human body skeleton model reconstruction method. It takes input from multi-view video, and computes the visual hull of human body through shape-from-silhouette. It then extracts the 3D skeleton by a new hybrid 2-subiteration thinning algorithm, and registers the skeleton to a 3D human body skeleton model by a heuristic method. The experiment results show that although the intermediate results of the shape-from-silhouettes process and 3D thinning process contain much noise, the model registration method, which bases on a set of simple prior rules , can still get accurate 3D human body skeleton model.