SHREC’14 Track: Shape Retrieval of Non-Rigid 3D Human Models

Published

June 12, 2014

Author(s)

Afzal A. Godil, Chunyuan Li

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.

Proceedings Title

The Seventh Eurographics Workshop on 3D Object Retrieval (3DOR 2014)

Conference Dates

April 6, 2014

Conference Location

Strasbourg

Conference Title

Co-event of the 35rd Annual Conference of the European Association for Computer Graphics (Eurographics 2014).

Pub Type

Conferences

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Keywords

non-rigid 3D shape retrieval algorithms, human models, variety of body shapes and poses

Citation

Godil, A. and Li, C. (2014), SHREC’14 Track: Shape Retrieval of Non-Rigid 3D Human Models, The Seventh Eurographics Workshop on 3D Object Retrieval (3DOR 2014) , Strasbourg, -1, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=915674 (Accessed October 18, 2025)