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

Pickup, David ORCID: https://orcid.org/0000-0003-2894-0822, Martin, Ralph Robert, Rosin, Paul L. ORCID: https://orcid.org/0000-0002-4965-3884, Sun, Xianfang ORCID: https://orcid.org/0000-0002-6114-0766, 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, H., Lai, L., Li, B., Li, C., Li, H., Litman, R., Liu, X., Liu, Z., Lu, Y, Tatsuma, A. and Ye, J. 2014. SHREC'14 Track: Shape retrieval of non-rigid 3D human models. Presented at: Eurographics Workshop on 3D Object Retrieval, Strasbourg, France, 6 April 2014. pp. 101-110. Item availability restricted.

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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.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics
Funders:	EPSRC
Related URLs:	http://3dor2014.ensea.fr/SHREC2014.html
Last Modified:	07 Nov 2024 13:00
URI:	https://orca.cardiff.ac.uk/id/eprint/60329

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