A New 3-D Model Retrieval System Based on Aspect-Transition Descriptor
Abstract
In this paper, we propose a new 3-D model retrieval system using the Aspect-Transition Descriptor which is based on the aspect graph representation [1,2] approach. The proposed method differs from the conventional aspect graph representation in that we utilize transitions as well as aspects. The process of generating the Aspect-Transition Descriptor is as follows: First, uniformly sampled views of a 3-D model are separated into a stable and an unstable view sets according to the local variation of their 2-D shape. Next, adjacent stable views and unstable views are grouped into clusters and we select the characteristic aspects and transitions by finding the representative view from each cluster. The 2-D descriptors of the selected characteristic aspects and transitions are concatenated to form the 3-D descriptor. Matching the Aspect-Transition Descriptor s is done using a modified Hausdorff distance. To evaluate the proposed 3-D descriptor, we have evaluated the retrieval performance on the Princeton benchmark database [3] and found that our method outperforms other retrieval techniques.
Cite
Text
Lee et al. "A New 3-D Model Retrieval System Based on Aspect-Transition Descriptor." European Conference on Computer Vision, 2006. doi:10.1007/11744085_42Markdown
[Lee et al. "A New 3-D Model Retrieval System Based on Aspect-Transition Descriptor." European Conference on Computer Vision, 2006.](https://mlanthology.org/eccv/2006/lee2006eccv-new/) doi:10.1007/11744085_42BibTeX
@inproceedings{lee2006eccv-new,
title = {{A New 3-D Model Retrieval System Based on Aspect-Transition Descriptor}},
author = {Lee, Soochahn and Yoon, Sehyuk and Yun, Il Dong and Kim, Duck Hoon and Lee, Kyoung Mu and Lee, Sang Uk},
booktitle = {European Conference on Computer Vision},
year = {2006},
pages = {543-554},
doi = {10.1007/11744085_42},
url = {https://mlanthology.org/eccv/2006/lee2006eccv-new/}
}