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.
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Lee, S., Yoon, S., Yun, I.D., Kim, D.H., Lee, K.M., Lee, S.U. (2006). A New 3-D Model Retrieval System Based on Aspect-Transition Descriptor . In: Leonardis, A., Bischof, H., Pinz, A. (eds) Computer Vision – ECCV 2006. ECCV 2006. Lecture Notes in Computer Science, vol 3954. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11744085_42
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DOI: https://doi.org/10.1007/11744085_42
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