Rights accessRestricted access - publisher's policy
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.
CitationAlcoverro, M. [et al.]. Connected Operators on 3D data for human body analysis. A: IEEE Conference on Computer Vision and Pattern Recognition. "2011 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops". 2011, p. 9-14.
All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder. If you wish to make any use of the work not provided for in the law, please contact: firstname.lastname@example.org