Local Goemetrical Feature with Spatial Context for Shape-based 3D Model Retrieval

Kawamura, Shun; Usui, Kazuya; Furuya, Takahiko; Ohbuchi, Ryutarou

Local Goemetrical Feature with Spatial Context for Shape-based 3D Model Retrieval

Files

055-058.pdf (469.86 KB)

Date

2012

Authors

Kawamura, Shun
Usui, Kazuya
Furuya, Takahiko
Ohbuchi, Ryutarou

Publisher

The Eurographics Association

Abstract

With recent popularity of 3D models, retrieval and recognition of 3D models based on their shape has become an important subject of study. This paper proposes a 3D model retrieval algorithm that is invariant to global deformation as well as to similarity transformation of 3D models. The algorithm is based on a set of local 3D geometrical features combined with bag-of-features approach. The algorithm employs a novel local feature, which is a combination of local geometrical feature enhanced with its spatial context computed as histogram of diffusion distance computed over mesh surface. Experimental evaluation of retrieval accuracy by using benchmark databases showed that adding positional context significantly improves retrieval accuracy.

        @inproceedings{:10.2312/3DOR/3DOR12/055-058
,
booktitle = {Eurographics Workshop on 3D Object Retrieval
},
editor = {M. Spagnuolo and M. Bronstein and A. Bronstein and A. Ferreira
},
title = {{Local Goemetrical Feature with Spatial Context for Shape-based 3D Model Retrieval
}},
author = {Kawamura, Shun and 
Usui, Kazuya and 
Furuya, Takahiko and 
Ohbuchi, Ryutarou
},
year = {2012
},
publisher = {The Eurographics Association
},
ISSN = {1997-0463
},
ISBN = {978-3-905674-36-1
},
DOI = {/10.2312/3DOR/3DOR12/055-058
}
}