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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.
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