2006 | OriginalPaper | Buchkapitel
A New 3-D Model Retrieval System Based on Aspect-Transition Descriptor
verfasst von : Soochahn Lee, Sehyuk Yoon, Il Dong Yun, Duck Hoon Kim, Kyoung Mu Lee, Sang Uk Lee
Erschienen in: Computer Vision – ECCV 2006
Verlag: Springer Berlin Heidelberg
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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.