Shape Retrieval of Non-Rigid 3D Human Models

Pickup, D.; Sun, X.; Rosin, P. L.; Martin, R. R.; Cheng, Z.; Lian, Z.; Aono, M.; Hamza, A. Ben; 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.; J.Ye,

Shape Retrieval of Non-Rigid 3D Human Models

Files

101-110.pdf (6.71 MB)

Date

2014

Publisher

The Eurographics Association

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.

        @inproceedings{:10.2312/3dor.20141056
https::/diglib.eg.org/handle/10.2312/3dor.20141056.101-110
,
booktitle = {Eurographics Workshop on 3D Object Retrieval
},
editor = {Benjamin Bustos and Hedi Tabia and Jean-Philippe Vandeborre and Remco Veltkamp
},
title = {{Shape Retrieval of Non-Rigid 3D Human Models
}},
author = {Pickup, D. and 
Sun, X. and 
Bu, S. and 
Castellani, U. and 
Cheng, S. and 
Garro, V. and 
Giachetti, A. and 
Godil, A. and 
Han, J. and 
Johan, H. and 
Lai, L. and 
Li, B. and 
Rosin, P. L. and 
Li, C. and 
Li, H. and 
Litman, R. and 
Liu, X. and 
Liu, Z. and 
Lu, Y. and 
Tatsuma, A. and 
J.Ye, and 
Martin, R. R. and 
Cheng, Z. and 
Lian, Z. and 
Aono, M. and 
Hamza, A. Ben and 
Bronstein, A. and 
Bronstein, M.
},
year = {2014
},
publisher = {The Eurographics Association
},
ISSN = {1997-0463
},
ISBN = {978-3-905674-58-3
},
DOI = {/10.2312/3dor.20141056
https://diglib.eg.org/handle/10.2312/3dor.20141056.101-110
}
}