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Connected operators on 3D data for human body analysis

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4 Author(s)

This paper presents a novel method for filtering and extraction of human body features from 3D data, either from multi-view images or range sensors. The proposed algorithm consists in processing the geodesic distances on a 3D surface representing the human body in order to find prominent maxima representing salient points of the human body. We introduce a 3D surface graph representation and filtering strategies to enhance robustness to noise and artifacts present in this kind of data. We conduct several experiments on different datasets involving 2 multi-view setups and 2 range data sensors: Kinect and Mesa SR4000. In all of them, the proposed algorithm shows a promising performance towards human body analysis with 3D data.

Published in:

Computer Vision and Pattern Recognition Workshops (CVPRW), 2011 IEEE Computer Society Conference on

Date of Conference:

20-25 June 2011