Discriminative sparse image models for class-specific edge detection and image interpretation

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5304 LNCS, Issue PART 3, 2008, Pages 43-56

  Mairal, Julien ^a,d   Leordeanu, Marius ^b   Bach, Francis ^a,d   Hebert, Martial ^b   Ponce, Jean ^c,d  

^a INRIA ROCQUENCOURT   (France)

^b CARNEGIE MELLON UNIVERSITY   (United States)

^c ECOLE NORMALE SUPÉRIEURE   (France)

^d CNRS   (France)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL EFFICIENCY; COMPUTER VISION; COST FUNCTIONS; IMAGE ANALYSIS; IMAGE SEGMENTATION; LEAST SQUARES APPROXIMATIONS; TEXTURES;

IMAGE INTERPRETATION; L1 REGULARIZATIONS; LEAST-SQUARES RECONSTRUCTION; LOCAL IMAGE DESCRIPTIONS; MULTISCALE METHOD; SPARSE SIGNAL MODELS; TEXTURE SEGMENTATION; VIDEO RESTORATION;

EDGE DETECTION;

EID: 56749154082     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-88690-7_4     Document Type: Conference Paper

References (27)

1. Aharon, M., Elad, M., Bruckstein, A.M.: The K-SVD: An algorithm for designing of overcomplete dictionaries for sparse representations. IEEE Trans. SP 54(11) (2006)
2. Arbelaez, P.: Boundary extraction in natural images using ultrametric contour maps. In: POCV 2006 (2006)
3. Canny, J.F.: A computational approach to edge detection. IEEE Trans. PAMI 8(6) (1986)
4. Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: Proc. CVPR (2005)
5. Dollar, P., Tu, Z., Belongie, S.: Supervised learning of edges and object boundaries. In: Proc. CVPR (2006)
6. Donoho, D.L.: Compressive sampling. IEEE Trans. IT 52(4) (2006)
7. Efron, B., Hastie, T., Johnstone, I., Tibshirani, R.: Least angle regression. Ann. Statist. 32(2) (2004)
8. Elad, M., Aharon, M.: Image denoising via sparse and redundant representations over learned dictionaries. IEEE Trans. IP 54(12) (2006)
9. Engan, K., Aase, S.O., Husoy, J.H.: Frame based signal compression using method of optimal directions (MOD). In: Proc. ISCS (1999)
10. Everingham, M., Van Gool, L., Williams, C.K.I., Winn, J., Zisserman, A.: The PASCAL Visual Object Classes Challenge 2007 (VOC 2007) Results (2007)
11. Lee, H., Battle, A., Rajat, R., Ng, A.Y.: Efficient sparse coding algorithms. In: Adv. NIPS (2007)
12. Leordeanu, M., Hebert, M., Sukthankar, R.: Beyond local appearance: Category recognition from pairwise interactions of simple features. In: Proc. CVPR (2007)
13. Luenberger, D.G.: Linear and Nonlinear Programming. Addison-Wesley, Reading (1984)
14. Mairal, J., Bach, F., Ponce, J., Sapiro, G., Zisserman, A.: Discriminative learned dictionaries for local image analysis. In: Proc. CVPR (2008)
15. Mairal, J., Elad, M., Sapiro, G.: Sparse representation for color image restoration. IEEE Trans. IP 17(1) (2008)
16. Maire, M., Arbelaez, P., Fowlkes, C., Malik, J.: Using Contours to Detect and Localize Junctions in Natural Images. In: Proc. CVPR (2008)
17. Mallat, S., Zhang, Z.: Matching pursuit in a time-frequency dictionary. IEEE Trans. SP 41(12) (1993)
18. Martin, D.R., Fowlkes, C.C., Malik, J.: Learning to detect natural image boundaries using local brightness, color, and texture cues. IEEE Trans. PAMI 26(1) (2004)
19. Martin, D., Fowlkes, C., Tal, D., Malik, J.: A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics. In: Proc. ICCV (2001)
20. Moghaddam, B., Weiss, Y., Avidan, S.: Spectral bounds for sparse pea: Exact and greedy algorithms. In: Adv. NIPS (2005)
21. Olshausen, B.A., Field, D.J.: Sparse coding with an overcomplete basis set: A strategy employed by vl? Vision Research 37 (1997)
22. Peyre, G.: Non-negative sparse modeling of textures. In: Sgallari, F., Murli, A., Paragios, N. (eds.) SSVM 2007. LNCS, vol. 4485. Springer, Heidelberg (2007)
23. Prasad, M., Zisserman, A., Fitzgibbon, A., Kumar, M.P., Torr, P.: Learning class-specifc edges for object detection and segmentation. In: Kalra, P.K., Peleg, S. (eds.) ICVGIP 2006. LNCS, vol. 4338. Springer, Heidelberg (2006)
24. Ranzato, M., Huang, F., Boureau, Y., LeCun, Y.: Unsupervised learning of invariant feature hierarchies with applications to object recognition. In: Proc. CVPR (2007)
25. Roth, S., Black, M.J.: Fields of experts: A framework for learning image priors. In: Proc. CVPR (2005)
26. Shawe-Taylor, J., Cristianini, N.: Kernel Methods for Pattern Analysis (2004)
27. Winn, J., Criminisi, A., Minka, T.: Object categorization by learned universal visual dictionary. In: Proc. ICCV (2005)