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Monocular 3D human body reconstruction towards depth augmentation of television sequences

Abstract:

This paper addresses the reconstruction of 3D human body models from 2D video sequences. Considering that the input frames are already segmented, the proposed technique consists of three stages. These stages are independently applied over each segmented frame. Firstly, a skeleton of a human figure obtained from the segmented image is extracted by means of a fast algorithm based on a Voronoi diagram of the boundary points. Afterwards, the skeleton is labelled according to the human body parts (e.g. head, upper arm, lower arm, torso, etc). Secondly, an initial 3D model posture is estimated from the labelled skeleton. Finally, an iterative closest point (ICP) implementation is used to refine the initial model posture by maximizing the similarity between the projected 3D model and the segmented image. Experimental results with video sequences are presented.