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SHREC'14 Track: Shape retrieval of non-rigid 3D human models

 
: Pickup, D.; Sun, X.; Rosin, P.L.; Martin, R.R.; Cheng, Z.; Lian, Z.; Aono, M.; Ben Hamza, A.; Bronstein, A.; Bronstein, M.; Bu, S.; Castellani, U.; Cheng, S.; Garro, V.; Giachetti, A.; Godil, A.; Han, J.; Johan, Henry; Lai, L.; Li, Bo; Li, C.; Li, H.; Litman, R.; Liu, X.; Liu, Z.; Lu, Y.; Tatsuma, A.; Ye, J.

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Bustos, Benjamin (Ed.) ; European Association for Computer Graphics -EUROGRAPHICS-:
Eurographics Workshop on 3D Object Retrieval, EG 3DOR 2014 : Strasbourg, France, April 6th, 2014
Aire-la-Ville: Eurographics Association, 2014
ISBN: 978-3-905674-58-3
S.101-110
Workshop on 3D Object Retrieval (EG 3DOR) <7, 2014, Straßbourg>
Englisch
Konferenzbeitrag
Fraunhofer IDM@NTU ()
shape retrieval; human models; 3D object retrieval; Business Field: Virtual engineering; Research Area: Computer graphics (CG); Research Area: Computer vision (CV)

Abstract
We have created a new benchmarking dataset for testing non-rigid 3D shape retrieval algorithms, one that is much more challenging than existing datasets. Our dataset features exclusively human models, in a variety of body shapes and poses. 3D models of humans are commonly used within computer graphics and vision, and so the ability to distinguish between body shapes is an important shape retrieval problem. In this track nine groups have submitted the results of a total of 22 different methods which have been tested on our new dataset.

: http://publica.fraunhofer.de/dokumente/N-445538.html