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Towards a parameterless 3D mesh segmentation

Farag, Sara, Abdelrahman, Wael, Nahavandi, Saeid and Creighton, Douglas 2013, Towards a parameterless 3D mesh segmentation, in ICGIP 2012 : Proceedings of the 4th International Conference on Graphic and Image Processing, SPIE, [Singapore], pp. 1-8, doi: 10.1117/12.2010891.

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Title Towards a parameterless 3D mesh segmentation
Author(s) Farag, Sara
Abdelrahman, Wael
Nahavandi, Saeid
Creighton, DouglasORCID iD for Creighton, Douglas orcid.org/0000-0002-9217-1231
Conference name Graphic and Image Processing. International Conference (4th : 2012 : Singapore)
Conference location Singapore
Conference dates 6-7 Oct. 2012
Title of proceedings ICGIP 2012 : Proceedings of the 4th International Conference on Graphic and Image Processing
Editor(s) Zhu, Zeng
Publication date 2013
Conference series Graphic and Image Processing International Conference
Start page 1
End page 8
Total pages 8
Publisher SPIE
Place of publication [Singapore]
Keyword(s) 3D mesh segmentation
3D mesh analysis
2D footprints
antipodal vertices
cognitive theory
Summary This paper proposes a novel technique for 3D mesh segmentation using multiple 2D pose footprints. Such problem has been targeted many times in the literature, but still requires further development especially in the area of automation. The proposed algorithm applies cognition theory and provides a generic technique to form a 3D bounding contour from a seed vertex on the 3D mesh. Forming the cutlines is done in both 2D and 3D spaces to enrich the available information for the search processes. The main advantage of this technique is the possibility to operate without any object-dependent parameters. The parameters that can be used will only be related to the used cognition theory and the seeds suggestion, which is another advantage as the algorithm can be generic to more than one theory of segmentation or to different criterion. The results are competitive against other algorithms, which use object-dependent or tuning parameters. This plus the autonomy and generality features, provides an efficient and usable approach for segmenting 3D meshes and at the same time to reduce the computation load.
ISBN 9780819495662
Language eng
DOI 10.1117/12.2010891
Field of Research 080103 Computer Graphics
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1 Full written paper - refereed
Persistent URL http://hdl.handle.net/10536/DRO/DU:30055216

Document type: Conference Paper
Collection: Centre for Intelligent Systems Research
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