Multi-scale object detection by clustering lines

Proceedings of the IEEE International Conference on Computer Vision

Volumn , Issue , 2009, Pages 484-491

  Ommer, Björn ^a   Malik, Jitendra ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA SETS; EDGE POINT; HIERARCHICAL APPROACH; LOCAL SCALE; MULTISCALES; NATURAL SCENES; OBJECT BOUNDARIES; OBJECT DETECTION; PAIRWISE CLUSTERING; SCALE SPACES; SPARSE REPRESENTATION; VOTING METHOD; VOTING TECHNIQUES;

OBJECT RECOGNITION;

COMPUTER VISION;

EID: 77953191017     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2009.5459200     Document Type: Conference Paper

References (35)

1. D. Ballard. Generalizing the hough transform to detect arbitrary shapes. Pattern Recognition, 13(2), 1981.
2. A. C. Berg, T. L. Berg, and J. Malik. Shape matching and object recognition using low distortion correspondence. In CVPR, pages 26-33, 2005.
3. A. C. Berg and J. Malik. Geometric blur for template matching. In CVPR, pages 607-614, 2001.
4. O. Boiman, E. Shechtman, and M. Irani. In defense of nearest-neighbor based image classification.CVPR'08.
5. C.-C. Chang and C.-J. Lin. LIBSVM: A library for support vector machines, 2001.
6. D. Comaniciu, V. Ramesh, and P. Meer. The variable bandwidth mean shift and data-driven scale selection. In ICCV, pages 438-445, 2001.
7. D. J. Crandall, P. F. Felzenszwalb, and D. P. Huttenlocher. Spatial priors for part-based recognition using statistical models. In CVPR, pages 10-17, 2005.
8. G. Csurka, C. R. Dance, L. Fan, J. Willamowski, and C. Bray. Visual categorization with bags of keypoints. In ECCV. Workshop Stat. Learn. in Comp. Vis., 2004.
9. N. Dalal and B. Triggs. Histograms of oriented gradients for human detection. In CVPR, pages 886-893, 2005.
10. M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman. The PASCAL Visual Object Classes Challenge 2008 (VOC2008) Results. http://www.pascal-network.org/challenges/VOC/voc2008/workshop.
11. P. F. Felzenszwalb and D. P. Huttenlocher. Pictorial structures for object recognition. IJCV, 61(1):55-79, 2005.
12. R. Fergus, P. Perona, and A. Zisserman. Object class recognition by unsupervised scale-invariant learning. In CVPR, pages 264-271, 2003.
13. V. Ferrari, L. Fevrier, F. Jurie, and C. Schmid. Groups of adjacent contour segments for object detection. PAMI, 30(1):36-51, 2008.
14. V. Ferrari, F. Jurie, and C. Schmid. Accurate object detection with deformable shape models learnt from images. In CVPR, 2007.
15. V. Ferrari, F. Jurie, and C. Schmid. From images to shape models for object detection. Technical Report 6600, INRIA, Grenoble, 2008.
16. K. Grauman and T. Darrell. The pyramid match kernel: Discriminative classification with sets of image features. In ICCV, 2005.
17. W. Grimson and D. Huttenlocher. On the sensitivity of the hough transform for object recognition. PAMI, 12(3):255-274, 1990.
18. T. Hofmann and J. M. Buhmann. Pairwise data clustering by deterministic annealing. PAMI, 19(1):1-14, 1997.
19. P. Hough. Method and means for recognizing complex patterns. U.S. Patent 3069654, 1962.
20. T. Kadir and M. Brady. Saliency, scale and image description. IJCV, 45(2), 2001.
21. C. H. Lampert, M. B. Blaschko, and T. Hofmann. Beyond sliding windows: Object localization by efficient subwindow search. In CVPR, 2008.
22. S. Lazebnik, C. Schmid, and J. Ponce. Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories. In CVPR, pages 2169-2178, 2006.
23. B. Leibe, A. Leonardis, and B. Schiele. Combined object categorization and segmentation with an implicit shape model. In ECCV. Workshop Stat. Learn. in Comp. Vis., 2004.
24. B. Leibe, A. Leonardis, and B. Schiele. Robust object detection with interleaved categorization and segmentation. IJCV, 77(1-3):259-289, 2008.
25. D. Lowe. Object recognition from local scale-invariant features. In ICCV, pages 1150-1157, 1999.
26. M. Maire, P. Arbelaez, C. Fowlkes, and J. Malik. Using contours to detect and localize junctions in natural images. In CVPR, 2008.
27. S. Maji and J. Malik. Object detection using a max-margin hough transform. In CVPR, 2009.
28. B. Ommer and J. M. Buhmann. Learning the compositional nature of visual objects. In CVPR, 2007.
29. B. Ommer, T. Mader, and J. Buhmann. Seeing the objects behind the dots: Recognition in videos from a moving camera. IJCV, 83(1):57-71, 2009.
30. A. Opelt, A. Pinz, and A. Zisserman. Incremental learning of object detectors using a visual shape alphabet. In CVPR, pages 3-10, 2006.
31. J. Shotton, A. Blake, and R. Cipolla. Contour-based learning for object detection. In ICCV, 2005.
32. J. Sivic, B. C. Russell, A. A. Efros, A. Zisserman, and W. T. Freeman. Discovering objects and their localization in images. In ICCV, pages 370-377, 2005.
33. E. B. Sudderth, A. B. Torralba, W. T. Freeman, and A. S. Willsky. Learning hierarchical models of scenes, objects, and parts. In ICCV, pages 1331-1338, 2005.
34. P. A. Viola and M. J. Jones. Robust real-time face detection. IJCV, 57(2):137-154, 2004.
35. Q. H. Zhu, L. M. Wang, Y. Wu, and J. B. Shi. Contour context selection for object detection: A set-to-set contour matching approach. In ECCV, 2008.