Reference : CPU-based real-time surface and solid voxelization for incomplete point cloud

	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Electrical & electronics engineering
	To cite this reference:	http://hdl.handle.net/10993/25019

Title :	CPU-based real-time surface and solid voxelization for incomplete point cloud
Language :	-
Author, co-author :	Garcia, Frederic D. [Interdisciplinary Centre for Security Reliability and Trust (SnT), University of Luxembourg, Luxembourg]
	Ottersten, Björn [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) >]
Publication date :	2014
Main document title :	Proceedings of the 22nd International Conference on Pattern Recognition
Publisher :	Institute of Electrical and Electronics Engineers Inc.
Pages :	2757-2762
Peer reviewed :	Yes
Audience :	International
Event name :	22nd International Conference on Pattern Recognition, ICPR 2014
Event date :	24 August 2014 through 28 August 2014
Keywords :	[en] Curve-skeleton ; Distance transform ; Point cloud ; Real-time ; Skeletonization ; Voxelization ; Computer graphics ; Computer vision ; Pattern recognition ; Curve skeletons ; Distance transforms ; Real time ; Three dimensional computer graphics
Abstract :	[en] This paper presents a surface and solid voxelization approach for incomplete point cloud datasets. Voxelization stands for a discrete approximation of 3-D objects into a volumetric representation, a process which is commonly employed in computer graphics and increasingly being used in computer vision. In contrast to surface voxelization, solid voxelization not only set those voxels related to the object surface but also those voxels considered to be inside the object. To that end, we first approximate the given point set, usually describing the external object surface, to an axis-aligned voxel grid. Then, we slice-wise construct a shell containing all surface voxels along each grid-axis pair. Finally, voxels inside the constructed shell are set. Solid voxelization results from the combination of all slices, resulting in a watertight and gap-free representation of the object. The experimental results show a high performance when voxelizing point cloud datasets, independently of the object's complexity, robust to noise, and handling large portions of data missing. © 2014 IEEE.
Permalink :	http://hdl.handle.net/10993/25019
DOI :	10.1109/ICPR.2014.475
Commentary :	109641 9781479952083

	File(s) associated to this reference
	Fulltext file(s): File Commentary Version Size Access Open access cpu-based.pdf Publisher postprint 1.57 MB View/Open

All documents in ORBi^lu are protected by a user license.

 

University of Luxembourg Library |  Feedback |  Legal notices Site Map