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Publication Citation: SHREC‰14 Track: Shape Retrieval of Non-Rigid 3D Human Models

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Author(s): Afzal A. Godil; Chunyuan Li;
Title: SHREC‰14 Track: Shape Retrieval of Non-Rigid 3D Human Models
Published: June 12, 2014
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.
Conference: Co-event of the 35rd Annual Conference of the European Association for Computer Graphics (Eurographics 2014).
Proceedings: The Seventh Eurographics Workshop on 3D Object Retrieval (3DOR 2014)
Pages: 10 pp.
Location: Strasbourg, -1
Dates: April 6, 2014
Keywords: non-rigid 3D shape retrieval algorithms; human models; variety of body shapes and poses
Research Areas: Data and Informatics, Information Delivery Systems, Information Technology, Imaging
PDF version: PDF Document Click here to retrieve PDF version of paper (7MB)