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Towards a parameterless 3D mesh segmentation

conference contribution
posted on 2013-01-01, 00:00 authored by Sara Farag, Wael Abdelrahman, Saeid Nahavandi, Douglas CreightonDouglas Creighton
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.

History

Event

Graphic and Image Processing. International Conference (4th : 2012 : Singapore)

Pagination

1 - 8

Publisher

SPIE

Location

Singapore

Place of publication

[Singapore]

Start date

2012-10-06

End date

2012-10-07

ISBN-13

9780819495662

Language

eng

Publication classification

E1 Full written paper - refereed

Editor/Contributor(s)

Z Zhu

Title of proceedings

ICGIP 2012 : Proceedings of the 4th International Conference on Graphic and Image Processing

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