3D object detection and viewpoint selection in sketch images using local patch-based zernike moments

7th International Workshop on Content-Based Multimedia Indexing, CBMI 2009

Volumn , Issue , 2009, Pages 189-194

  Ta, Anh Phuong ^a   Wolf, Christian ^a   Lavoué, Guillaume ^a   Baskurt, Atilla ^a  

^a UNIVERSITÉ DE LYON   (France)

Author keywords

2D 3D object detection; Local features; Localization and recognition; Pose recognition; Rotation angle retrieval

Indexed keywords

FEATURE EXTRACTION; INDEXING (OF INFORMATION); OBJECT RECOGNITION;

3-D OBJECT DETECTIONS; LOCAL FEATURE; LOCALIZATION AND RECOGNITION; POSE RECOGNITION; PRODUCTION PROCESS; ROTATION ANGLES; SPATIAL CONSTRAINTS; VIEWPOINT SELECTION;

OBJECT DETECTION;

EID: 70350349670     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CBMI.2009.29     Document Type: Conference Paper

References (18)

1. T. F. Ansary, M. Daoudi, and J.-P. Vandeborre. A bayesian 3-d search engine using adaptive views clustering. IEEE Transactions on Multimedia, 9(1):78-88, 2007.
2. S. Belongie, J. Malik, and J. Puzicha. Shape matching and object recognition using shape contexts. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 24(4):509-522, 2002.
3. M. Brown, R. Szeliski, and S. A. J. Winder. Multi-image matching using multi-scale oriented patches. In CVPR (1), pages 510-517, 2005.
4. A. Choksuriwong, H. Laurent, C. Rosenberger, and C. Maaoui. Object recognition using local characterisation and zernike moments. In ACIVS, pages 108-115, 2005.
5. R. Fergus, P. Perona, and A. Zisserman. Object class recognition by unsupervised scale-invariant learning. In CVPR (2), pages 264-271, 2003.
6. V. Ferrari, L. Fevrier, F. Jurie, and C. Schmid. Groups of adjacent contour segments for object detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(1):36-51, 2008.
7. D. Hoiem, C. Rother, and J. Winn. 3d layoutcrf for multi-view object class recognition and segmentation. In Computer Vision and Pattern Recognition, 2007. CVPR'07. IEEE Conference on, pages 1-8, 2007.
8. S. Hou and K. Ramani. Calligraphic interfaces: Classifier combination for sketch-based 3d part retrieval. Comput. Graph., 31(4):598-609, 2007.
9. S.-H. Kim, I.-S. Kweon, and I.-C. Kim. Probabilistic model-based object recognition using local zernike moments. In MVA, pages 334-337, 2002.
10. V. Kolmogorov and R. Zabih. What energy functions can be minimized via graph cuts? IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(2):147-159, 2004.
11. D. G. Lowe. Object recognition from local scale-invariant features. In ICCV, pages 1150-1157, 1999.
12. A. Opelt, A. Pinz, and A. Zisserman. Incremental learning of object detectors using a visual shape alphabet. In CVPR (1), pages 3-10, 2006.
13. J. Revaud, G. Lavoué, and A. Baskurt. Improving zernike moments comparison for optimal similarity and rotation angle retrieval. IEEE Transactions on Pattern Analysis and Machine Intelligence, 31(4):627-636, 2009.
14. J. Shotton, A. Blake, and R. Cipolla. Contour-based learning for object detection. In ICCV, pages 503-510, 2005.
15. T.S. Caetano, T. Caelli, D. Schuurmans, and D. Barone. Graphical models and point pattern matching. IEEE Transactions on Pattern Analysis and Machine Intelligence, 28(10):1646-1663, 2006.
16. H. Wang and E. R. Hancock. A kernel view of spectral point pattern matching. In Joint Int'l Workshops Syntactical and Structural Pattern Recognition and Statistical Pattern Recognition (SSPR-SPR), pages 361-369, 2004.
17. C. Wolf, J. Jolion, W. Kropatsch, and H. Bischof. Content Based Image Retrieval using Interest Points and Texture Features. In Proceedings of the International Conference on Pattern Recognition, volume 4, pages 234-237, 2000.
18. W. Zhang and J. Kosecka. Generalized ransac framework for relaxed correspondence problems. In 3DPVT, pages 854-860, 2006.