Abstract
Characteristic view is an effective way to represent a 3D object through a set of distinct projections from different view aspects. In this paper, we proposed techniques for automatic characteristic views generations by clustering views of the object from multiple view aspect. By considering the resulting clusters as View Topics that describe a set of portraits of the object, the object can be represented by a set of view topics that can be applied to 3D object retrieval with similarity measures based on the Vector Space Model and the Language Model as well as advanced techniques such as RBF Kernel method. Our experiments have demonstrated that our method is not only invariant with respect to rotation and scaling, but also invariant with respect to the object reflection, and achieve an overall better performance than existing methods. Copyright © 2009 ACM.
| Original language | English |
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| Title of host publication | CIVR 2009 - Proceedings of the ACM International Conference on Image and Video Retrieval |
| Pages | 20-27 |
| DOIs | |
| Publication status | Published - 2009 |
| Event | ACM International Conference on Image and Video Retrieval, CIVR 2009 - Santorini Island, Greece Duration: 8 Jul 2009 → 10 Jul 2009 |
Conference
| Conference | ACM International Conference on Image and Video Retrieval, CIVR 2009 |
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| Place | Greece |
| City | Santorini Island |
| Period | 8/07/09 → 10/07/09 |
Research Keywords
- 3D object representation
- 3D object retrieval
- Characteristic views
- Curvature scale space images
- Projection images
- View topics