SHREC'12 track: Sketch-based 3D shape retrieval

Eurographics Workshop on 3D Object Retrieval, EG 3DOR

Volumn , Issue , 2012, Pages 109-118

  Li, B ^a,h   Schreck, T ^b   Godil, A ^a   Alexa, M ^c   Boubekeur, T ^d   Bustos, B ^e   Chen, J ^f   Eitz, M ^c   Furuya, T ^g   Hildebrand, K ^c   Huang, S ^f   Johan, H ^h   Kuijper, A ⁱ   Ohbuchi, R ^f   Richter, R ^c   Saavedra, J M ^e   Scherer, M ^j   Yanagimachi, T ^f   Yoon, G J ^k   Yoon, S M ^l  

^a NATIONAL INSTITUTE OF STANDARDS AND TECHNOLOGY   (United States)

^b UNIVERSITY OF KONSTANZ   (Germany)

^c TECHNISCHE UNIVERSITÄT BERLIN   (Germany)

^d TELECOM PARISTECH   (France)

^e UNIVERSITY OF CHILE   (Chile)

^f UNIVERSITY OF YAMANASHI   (Japan)

^g NISCA Co Ltd   (Japan)

^h NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

ⁱ FRAUNHOFER IGD   (Germany)

^j DARMSTADT UNIVERSITY OF TECHNOLOGY   (Germany)

^k National Institute for Mathematical Sciences   (South Korea)

^l Yonsei University   (South Korea)

more..

Author keywords

[No Author keywords available]

Indexed keywords

3D MODEL RETRIEVAL; 3D OBJECT RETRIEVAL; 3D SHAPE RETRIEVAL; COMPARATIVE EVALUATIONS; RESEARCH TOPICS; RETRIEVAL ACCURACY; RETRIEVAL PERFORMANCE; SKETCH-BASED 3D MODELING;

INFORMATION RETRIEVAL;

THREE DIMENSIONAL;

EID: 84883505145     PISSN: 19970463     EISSN: 19970471     Source Type: Conference Proceeding    
DOI: 10.2312/3DOR/3DOR12/109-118     Document Type: Conference Paper

References (25)

1. BELONGIE S., MALIK J., PUZICHA J.: Shape matching and object recognition using shape contexts. IEEE Trans. Pattern Anal. Mach. Intell. 24, 4 (2002), 509-522.
2. CHEN S., DONOHO D., SAUNDERS M.: Atomic decomposition by basis pursuit. SIAM journal on scientific computing 20, 1 (1999), 33-61.
3. COLE F., GOLOVINSKIY A., LIMPAECHER A., BARROS H. S., FINKELSTEIN A., FUNKHOUSER T. A., RUSINKIEWICZ S.: Where do people draw lines? ACM Trans. Graph. 27, 3 (2008), 1-11.
4. COLE F., SANIK K., DECARLO D., FINKELSTEIN A., FUNKHOUSER T. A., RUSINKIEWICZ S., SINGH M.: How well do line drawings depict shape? ACM Trans. Graph. 28, 3 (2009), 1-9.
5. 1 minimization. Proc. Nat. Aca. Sci. 100, 5 (2003), 2197-2202.
6. DECARLO D., FINKELSTEIN A., RUSINKIEWICZ S., SANTELLA A.: Suggestive contours for conveying shape. ACM Trans. Graph. 22, 3 (2003), 848-855.
7. DALAL N., TRIGGS B.: Histograms of oriented gradients for human detection. In CVPR (2005), pp. 886-893.
8. EITZ M., HILDEBRAND K., BOUBEKEUR T., ALEXA M.: Sketch-based 3D shape retrieval. In SIGGRAPH Talks (2010).
9. EITZ M., HILDEBRAND K., BOUBEKEUR T., ALEXA M.: Sketch-based image retrieval: Benchmark and bag-of-features descriptors. IEEE Trans. Vis. Comput. Graph. 17, 11 (2011), 1624-1636.
10. FURUYA T., OHBUCHI R.: Dense sampling and fast encoding for 3D model retrieval using bag-of-visual features. In CIVR (2009).
11. KUHN H. W.: The Hungarian method for the assignment problem. In 50 Years of Integer Programming 1958-2008. 2010, pp. 29-47.
12. LEE H., BATTLE A., RAINA R., NG A. Y.: Efficient sparse coding algorithms. In Advances in Neural Information Processing Systems 19, Schölkopf B., Platt J., Hoffman T., (Eds.). MIT Press, Cambridge, MA, 2007, pp. 801-808.
13. LI B., GODIL A., AONO M., BAI X., FURUYA T., LI L., LÓPEZ-SASTRE R., JOHAN H., OHBUCHI R., REDONDO-CABRERA C., TATSUMA A., YANAGIMACHI T., ZHANG S.: SHREC'12 track: Generic 3D shape retrieval. In 3DOR (2012), pp. 1-8.
14. LI B., JOHAN H.: View context: A 3D model feature for retrieval. In: S. Boll et al. (eds.): MMM 2010, LNCS, Springer, Heidelberg 5916 (2010), 185-195.
15. LI B., JOHAN H.: Sketch-based 3D model retrieval by incorporating 2D-3D alignment. Multimedia Tools and Applications (2012), 1-23 (online first version).
16. OHBUCHI R., FURUYA T.: Scale-weighted dense bag of visual features for 3D model retrieval from a partial view 3D model. In IEEE ICCV 2009 workshop on Search in 3D and Video (S3DV) (2009), pp. 63-70.
17. SAAVEDRA J., BUSTOS B.: An improved histogram of edge local orientations for sketch-based image retrieval. In Pattern Recognition, Vol. 6376 of Lec. Notes in Computer Science. 2010, pp. 432-441.
18. http://www.itl.nist.gov/iad/vug/sharp/contest/2012/SBR/, 2012.
19. SAAVEDRA J., BUSTOS B., SCHRECK T., YOON S. M.: Sketch-based 3D model retrieval using keyshapes for global and local representation. In Eurographics Wokshop on 3D Object Retrieval (Submitted) (2012).
20. SHILANE P., MIN P., KAZHDAN M. M., FUNKHOUSER T. A.: The Princeton shape benchmark. In SMI (2004), pp. 167-178.
21. SNODGRASS J. G., VANDERWART M.: A standardized set of 260 pictures: norms for name agreement, image agreement, familiarity, and visual complexity. Journal of Experimental Pyschology: Human Learning and Memory 6, 2 (1980), 174-215.
22. VELTKAMP R. C., TER HAAR F. B.: SHREC 2007 3D Retrieval Contest. Technical Report UU-CS-2007-015, Department of Information and Computing Sciences, Utrecht University, 2007.
23. YOON S. M., GRAF H.: Automatic skeleton extraction and splitting of target objects. In ICIP (2009), pp. 2421-2424.
24. YOON S. M., KUIJPER A.: View-based 3D model retrieval using compressive sensing based classification. In the 7th International Symposium on Image and Signal Processing and Analysis, ISPA 2011 (2011), IEEE, pp. 437-442.
25. YOON S. M., SCHERER M., SCHRECK T., KUIJPER A.: Sketch-based 3D model retrieval using diffusion tensor fields of suggestive contours. In ACM Multimedia (2010), pp. 193-200.