Appearance-based keypoint clustering

2009 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2009

Volumn , Issue , 2009, Pages 1279-1286

  Estrada, Francisco J ^b   Fua, Pascal ^a   Lepetit, Vincent ^a   Susstrunk, Sabine ^a  

^a EPFL   (Switzerland)

^b UNIVERSITY OF TORONTO   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTERING ALGORITHMS; IMAGE ENHANCEMENT;

APPEARANCE BASED; CLUSTERING METHODS; KEYPOINT; KEYPOINTS; MATCHING PROBLEMS;

COMPUTER VISION;

EID: 70450164392     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPRW.2009.5206514     Document Type: Conference Paper

References (27)

1. D. Comaniciu and P.Meer. A robust approach toward feature space analysis. PAMI, 24(5):603-619, 2002.
2. F. Estrada. Advances in computational image segmentation and perceptual grouping, 2005. Ph.D. Thesis, Dept. of Computer Science, University of Toronto.
3. F. Estrada and A. Jepson. Quantitative evaluation of a novel image segmentation algorithm. In CVPR, pages 1132-1139, 2005.
4. F. Estrada, A. Jepson, and C. Chennubhotla. Spectral embedding and min-cut for image segmentation. In BMVC, pages 317-326, 2004.
5. C. Fowlkes, D. Martin, and J. Malik. Learning affinity functions for image segmentation: Combining patch-based and gradient-based approaches. In CVPR, volume 2, pages 54- 61, 2003.
6. K. Fukunaga and L. Hostetler. The estimation of the gradient of a density function with applications in pattern recognition. In IEEE Trans. in Information Theory, volume IT-21, pages 32-40, 1975.
7. M. Galun, E. Sharon, R. Basri, and A. Brandt. Texture segmentation by multiscale aggregation of filter responses and shape elements. In ICCV, pages 716-723, 2003.
8. Y. Gdalyahu, D. Weinshall, and M. Werman. Selforganization in vision: Stochastic clustering for image segmentation, perceptual grouping, and image database organization. PAMI, 23(10):1053-1074, 2001.
9. L. Grady. Random walks for image segmentation. PAMI, 28(11):1768-1783, 2006.
10. G. Guy and G.Medioni. Inferring global perceptual contours from local features. IJCV, 13(9):920-935, 1996.
11. N. Jojic, B. J. Frey, and A. Kannan. Epitomic analysis of appearance and shape. In ICCV, pages 34-41, 2003.
12. A. Kannan, J. Winn, and C. Rother. Clustering appearance and shape by learning jigsaws. In NIPS, pages 657-664, 2006.
13. D. Lowe. Distinctive image festures from scale-invariant keypoints. IJCV, 60(2):91-110, 2004.
14. D. Lowe. Demo software: Sift keypoint detector, 2005. http://www.cs.ubc.ca/~lowe/keypoints/.
15. J. Malik, S. Belongie, J. Shi, and T. K. Leung. Textons, contours and regions: Cue integration in image segmentation. In ICCV, volume 2, pages 918-925, 1999.
16. D. Martin, C. Fowlkes, D. Tal, and J. Malik. A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics. In ICCV, pages 416-423, 2001.
17. M. Meila and J. Shi. Learning segmentation by random walks. In NIPS, pages 873-879, 2000.
18. K. Mikolajczyk and C. Schmid. A performance evaluation of local descriptors. PAMI, 27(10):1615-1630, 2005.
19. B. Micusik and T. Pajdla. Multi-label image segmentation via max-sum solver. In CVPR, pages 1-6, 2007.
20. M. Ozuysal, V. Lepetit, F. Fleuret, and P. Fua. Feature targeting for tracking by detection. In ECCV, pages 592-605, 2006.
21. Y. Rubner, J. Puzicha, C. Tomasi, and J.M. Buhman. Empirical evaluation of dissimilarity measures for color and texture. CVIU, 84(1):25-43, 2001.
22. J. Shi and J. Malik. Normalized cuts and image segmentation. PAMI, 22(8):888-905, 2000.
23. O. Tuzel, F. Porikli, and P. Meer. Region covariance: a fast descriptor for detection and classification. In ECCV, volume 2, pages 589-600, 2006.
24. M. Varma and A. Zisserman. A statistical approach to texture classification from single images. IJCV, 62(1-2):61-81, 2005.
25. M. Wertheimer. A Sourcebook of Gestalt Psychology. Routledge and Kegan Paul, 1938.
26. L. R. Williams and D. W. Jacobs. Stochastic completion fields: A neuralmodel of illusory contour shape and salience. Neural Computation, 9(4):837-858, 1997.
27. L. Yang, P. Meer, and D. J. Foran. Multiple class segmentation using a unified framework over mean-shift patches. In CVPR, pages 1-8, 2007.