Reference : Real-time Curve-skeleton Extraction of Human-scanned Point Clouds

	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science
	To cite this reference:	http://hdl.handle.net/10993/20667

Title :	Real-time Curve-skeleton Extraction of Human-scanned Point Clouds
Language :	English
Author, co-author :	Garcia, Frederic []
	Ottersten, Björn [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Publication date :	2015
Main document title :	International Conference on Computer Vision Theory and Applications (VISAPP 2015)
Pages :	54-60
Peer reviewed :	Yes
Audience :	International
Event name :	International Conference on Computer Vision Theory and Applications (VISAPP 2015)
Event date :	from 11-03-2015 to 14-03-2015
Event place (city) :	Berlin
Event country :	Germany
Keywords :	[en] Curve-skeleton ; Skeletonization ; Human Pose Estimation, ; Object Representation ; Point Cloud ; Real-time
Abstract :	[en] This paper presents a practical and robust approach for upright human curve-skeleton extraction. Curve skeletons are object descriptors that represent a simplified version of the geometry and topology of a 3-D object. The curve-skeleton of a human-scanned point set enables the approximation of the underlying skeletal structure and thus, to estimate the body configuration (human pose). In contrast to most curve-skeleton extraction methodologies from the literature, we herein propose a real-time curve-skeleton extraction approach that applies to scanned point clouds, independently of the object’s complexity and/or the amount of noise within the depth measurements. The experimental results show the ability of the algorithm to extract a centered curve-skeleton within the 3-D object, with the same topology, and with unit thickness. The proposed approach is intended for real world applications and hence, it handles large portions of data missing due to occlusions, acquisition hindrances or registration inaccuracies.
Target :	Researchers ; Professionals ; Students ; General public
Permalink :	http://hdl.handle.net/10993/20667

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