Semantics-driven approach for automatic selection of best views of 3D shapes

Eurographics Workshop on 3D Object Retrieval, EG 3DOR

Volumn , Issue , 2010, Pages 15-21

  Laga, Hamid ^a  

^a Global Edge Institute   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

3-D MODELING; AUTOMATIC SELECTION; BEST VIEW SELECTIONS; DATA-DRIVEN APPROACH; DIFFERENT CLASS; FEATURE SELECTION PROBLEM; LIGHT FIELDS; SALIENT FEATURES;

BENCHMARKING; SEMANTICS;

THREE DIMENSIONAL;

EID: 78650462475     PISSN: 19970463     EISSN: 19970471     Source Type: Conference Proceeding    
DOI: 10.2312/3DOR/3DOR10/015-022     Document Type: Conference Paper

References (19)

1. [ADV07] ANSARY T. F., DAOUDI M., VANDEBORRE J.-P.: A bayesian 3-d search engine using adaptive views clustering. IEEE Transactions on Multimedia 9, 1 (2007), 78-88.
2. [CTSO03] CHEN D.-Y., TIAN X.-P., SHEN Y.-T., OUHYOUNG M.: On visual similarity based 3D model retrieval. Computer Graphics Forum 22, 3 (2003), 223-232. 3, 4.
3. [DDA 04] DENTON T., DEMIRCI M. F., ABRAHAMSON J., SHOKOUFANDEH A., DICKINSON S.: Selecting canonical views for view-based 3-D object recognition. International Conference on Pattern Recognition 2 (2004), 273-276. 2.
4. [FCODS08] FU H., COHEN-OR D., DROR G., SHEFFER A.: Upright orientation of man-made objects. In SIGGRAPH '08: ACM SIGGRAPH 2008 papers (New York, NY, USA, 2008), ACM, pp. 1-7. 2, 5, 6.
5. [Kar10] KARYPIS G.: Metis - family of multilevel partitioning algorithms. http://glaros.dtc.umn.edu/gkhome/views/metis, 1 2010. 4.
6. [LN08] LAGA H., NAKAJIMA M.: Supervised Learning of Salient 2D Views of 3D Models. The Journal of the Society for Art and Science 7, 4 (December 2008), 124 -131. 3.
7. [LVJ05] LEE C. H., VARSHNEY A., JACOBS D. W.: Mesh saliency. In SIGGRAPH '05: ACM SIGGRAPH 2005 Papers (New York, NY, USA, 2005), ACM Press, pp. 659-666. 1, 2.
8. [MA00] MOKHTARIAN F., ABBASI S.: Automatic selection of optimal views in multi-view object recognition. In In The British Machine Vision Conf. (BMVCA f00), IEEE Computer Society, 272-281. NDR. National (2000), pp. 272-281. 5.
9. [MS09] MORTARA M., SPAGNUOLO M.: Semantics-driven best view of 3D shapes. Computers and Graphics 33, 3 (2009), 280- 290. 2.
10. [PPB 05] POLONSKY O., PATANÈ G., BIASOTTI S., GOTSMAN C., SPAGNUOLO M.: What's in an image? Towards the Computation of the "Best" View of an Object. The Visual Computer (Proceedings of Pacific Graphics) 21, 8-10 (2005), 840-847. 1, 2.
11. [PSG 06] PODOLAK J., SHILANE P., GOLOVINSKIY A., RUSINKIEWICZ S., FUNKHOUSER T.: A planar-reflective symmetry transform for 3D shapes. 549-559. 2.
12. [SF06] SHILANE P., FUNKHOUSER T.: Selecting Distinctive 3D Shape Descriptors for Similarity Retrieval. IEEE International Conference on Shape Modeling and Applications (SMI2006) (2006), 18.
13. [SF07] SHILANE P., FUNKHOUSER T.: Distinctive regions of 3D surfaces. ACM Transactions on Graphics 26, 2 (e 07), 7. 2, 3, 4.
14. [SMKF04] SHILANE P., MIN P., KAZHDAN M., FUNKHOUSER T.: The princeton shape benchmark. In SMI'04: Proceedings of the Shape Modeling International 2004 (SMI'04) (june 2004), pp. 167-178. 5.
15. [TFTN05] TAKAHASHI S., FUJISHIRO I., TAKESHIMA Y., NISHITA T.: A feature-driven approach to locating optimal viewpoints for volume visualization. In IEEE Visualization Conference (VIS2005) (2005), IEEE Computer Society, p. 63. 2.
16. [Vez10] VEZHNEVET A.: Gml adaboost matlab toolbox. http://graphics.cs. msu.ru/ru/science/research/machinelearning/adaboosttoolbox, 1 2010. 5.
17. [VFSH03] VÁZQUEZ P.-P., FEIXAS M., SBERT M., HEIDRICH W.: Automatic view selection using viewpoint entropy and its applications to image-based modelling. Computer Graphics Forum 22, 4 (2003), 689-700. 1, 2.
18. [WSY 09] WANG L., SUGIYAMA M., YANG C., HATANO K., FENG J.: Theory and algorithm for learning with dissimilarity functions. Neural Computation 21, 5 (2009), 1459-1484. 5.
19. [YSY 06] YAMAUCHI H., SALEEM W., YOSHIZAWA S., KARNI Z., BELYAEV A., SEIDEL H.-P.: Towards stable and salient multi-view representation of 3D shapes. In Proceedings of the IEEE International Conference on Shape Modeling and Applications 2006 (SMI'06) (2006), p. 40. 2, 4, 5