A new 3-D model retrieval system based on aspect-transition descriptor

  • Authors:

  • Soochahn Lee;Sehyuk Yoon;Il Dong Yun;Duck Hoon Kim;Kyoung Mu Lee;Sang Uk Lee

  • Affiliations:

  • School of Electrical Engineering and Computer Science, Seoul National University, Seoul, Republic of Korea;Service Planning Department, KT corporation, Seognam, Kyonggi-do, Republic of Korea;School of Electronics and Information Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea;Institute for Robotics and Intelligent Systems, University of Southern California, Los Angeles, CA;School of Electrical Engineering and Computer Science, Seoul National University, Seoul, Republic of Korea;School of Electrical Engineering and Computer Science, Seoul National University, Seoul, Republic of Korea

  • Venue:
  • ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
  • Year:
  • 2006

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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 Descriptors 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.