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Authors: Francisco A. Madera ; Enrique Ayala and Francisco Moo-Mena

Affiliation: Facultad de Matematicas and Universidad Autonoma de Yucatan, Mexico

ISBN: 978-989-758-087-1

Keyword(s): Collision Detection, Human Animation, Approximation with Spheres.

Related Ontology Subjects/Areas/Topics: Animation and Simulation ; Character Animation ; Collision Detection ; Computer Vision, Visualization and Computer Graphics ; Geometric Computing ; Geometry and Modeling ; Human Figure Animation ; Interactive Environments

Abstract: An algorithm to detect self-collisions in a human object is presented. We proposed to approximate the human object by spheres, which are placed inside the object mesh to fill the correspondent volume. We introduce the concept of sphere chain, a set of joined spheres which contains some regions of the human mesh. The object is approximated by several chains in the preprocessing stage to be prepared for the running stage to perform the collision detection.

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Paper citation in several formats:
A. Madera, F.; Ayala, E. and Moo-Mena, F. (2015). Self-collision Detection using Sphere Chains.In Proceedings of the 10th International Conference on Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2015) ISBN 978-989-758-087-1, pages 325-331. DOI: 10.5220/0005301603250331

@conference{grapp15,
author={Francisco A. Madera. and Enrique Ayala. and Francisco Moo{-}Mena.},
title={Self-collision Detection using Sphere Chains},
booktitle={Proceedings of the 10th International Conference on Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2015)},
year={2015},
pages={325-331},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005301603250331},
isbn={978-989-758-087-1},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2015)
TI - Self-collision Detection using Sphere Chains
SN - 978-989-758-087-1
AU - A. Madera, F.
AU - Ayala, E.
AU - Moo-Mena, F.
PY - 2015
SP - 325
EP - 331
DO - 10.5220/0005301603250331

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