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Proceedings Paper

Towards a parameterless 3D mesh segmentation
Author(s): Sara Farag; Wael Abdelrahman; Saeid Nahavandi; Douglas Creighton
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Paper Abstract

This paper proposes a novel technique for 3D mesh segmentation using multiple 2D pose footprints. Such a 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.

Paper Details

Date Published: 20 March 2013
PDF: 8 pages
Proc. SPIE 8768, International Conference on Graphic and Image Processing (ICGIP 2012), 87682O (20 March 2013); doi: 10.1117/12.2010891
Show Author Affiliations
Sara Farag, Deakin Univ. (Australia)
Wael Abdelrahman, Deakin Univ. (Australia)
Saeid Nahavandi, Deakin Univ. (Australia)
Douglas Creighton, Deakin Univ. (Australia)


Published in SPIE Proceedings Vol. 8768:
International Conference on Graphic and Image Processing (ICGIP 2012)
Zeng Zhu, Editor(s)

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