Learning coupled conditional random field for image decomposition with application on object categorization

26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR

Volumn , Issue , 2008, Pages

  Ma, Xiaoxu ^a   Grimson, W Eric L ^a  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER VISION; FEATURE EXTRACTION; FUSION REACTIONS; IMAGE PROCESSING; IMAGE SEGMENTATION; NUCLEAR PHYSICS; PATTERN RECOGNITION; RANDOM PROCESSES; TEXTURES; VISUAL COMMUNICATION;

COMPUTATIONAL MODELLING; COMPUTATIONAL SYSTEMS; CONDITIONAL RANDOM FIELD; IMAGE DECOMPOSITION; LOW-LEVEL CUES; MODEL LEARNING; NATURAL IMAGES; OBJECT CATEGORIZATION; RANDOM FIELDS; SINGLE LAYERS; STATE-OF-THE-ART METHODS; TRAINING SAMPLES; VISUAL CUES; VISUAL INFORMATIONS;

NEMATIC LIQUID CRYSTALS;

EID: 52249102022     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2008.4587593     Document Type: Conference Paper

References (28)

1. R. Abadi, J. J. Kulikowski, and P. Meudell. Visual performance in a case of visual agnosia. In Functional Recovery from Brain Damage. 1981. 1
2. L. Battelli and G. Sartori. Dissociation between contour-based and texture-based shape perception: A single case study. Visual Cognition, 4(3):275-310, 1997. 1
3. S. Belongie, J. Malik, and J. Puzicha. Shape matching and object recognition using shape contexts. IEEE Trans. PAMI, 24(24):590-522, April 2002. 1
4. J. Besag. Statistical analysis of non-lattice data. The Statistician, 24:179-195, 1975. 3
5. A. Bosch, A. Zisserman, and X. Munoz. Image classification using random forests and ferns. In ICCV, 2007. 8
6. J. Canny. A computational approach to edge detection. IEEE Trans. PAMI, 8(6):679-698, 1986. 4
7. L. Cao and L. Fei-Fei. Spatially coherent latent topic model for concurrent object segmentation and classification. In ICCV, 2007. 7
8. T. F. Cootes, G. J. Edwards, and C. J. Taylor. Active appearance models. PAMI, 23(6):853-857, 2001. 1
9. N. Cristianini, J. Shawe-Taylor, A. Elisseeff, and J. Kandola. On kernel-target alignment. In NIPS, 2001. 7
10. C. Dance, J. Willamowski, L. Fan, C. Bray, and G. Csurka. Visual categorization with bags of keypoints. ECCV Workshop on Statistical Learning in Computer Vision, 2004. 1
11. L. Fei-Fei, R. Fergus, and P. Perona. Learning generative visual models from few training examples. In IEEE. CVPR 2004, Workshop on GMBV, 2004. 7
12. R. Fergus, P. Perona, and A. Zisserman. Object class recognition by unsupervised scale-invariant learning. In CVPR, 2003. 1
13. A. Frome, Y. Singer, F. Sha, and J. Malik. Learning globally-consistent local distance functions for shape-based image retrieval and classification. In ICCV, 2007. 7
14. G. Griffin, A. Holub, and P. Perona. Caltech-256 object category dataset. Technical Report 7694, CIT, 2007. 7
15. T. Hofmann. Unsupervised learning by probabilistic latent semantic analysis. Machine Learning, 42(2), 2001. 3
16. S. Hoi, M. Lyu, and E. Chang. Learning the unified kernel machines for classification. In KDD, 2006. 7
17. S. Kumar and M. Hebert. Discriminative random fields: A discriminative framework for contextual interaction in classification. In ICCV, 2003. 2
18. S. Lazebnik, C. Schmid, and J. Ponce. Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories. In CVPR, 2006. 6
19. D. G. Lowe. Three-dimensional object recognition from single two-dimensional images. Artificial Intelligence, 1987. 1
20. D. G. Lowe. Distinctive image features from scale-invariant keypoints. IJCV, 60(2):91 - 110, November 2004. 6
21. X. Ma. http://people.csail.mit.edu/xiaoxuma. PhD thesis, MIT, 2008. 4, 7
22. J. Malik, S. Belongie, T. Leung, and J. Shi. Contour and texture analysis for image segmentation. IJCV, 2001. 1, 4
23. D. Martin, C. Fowlkes, and J. Malik. Learning to detect natural image boundaries using local brightness, color, and texture cues. IEEE Trans. PAMI, 26(5):530-549, 2004. 1, 4
24. M. J. Riddoch and G. W. Humphreys. A case study of integrative visual agnosia. Brain, 110(6):1431-1462, 1987. 1
25. C. Schmid and R. Mohr. Local grayvalue invariants for image retrieval. IEEE Trans. PAMI, 19(5):530-535, 1997. 1
26. A. Sha'ashua and S. Ullman. Structural saliency: The detection of globally salient structures using a locally connected network. In ICCV, 1988. 1
27. J. Shotton, A. Blake, and R. Cipolla. Contour-based learning for object detection. In ICCV, 2005. 6
28. M. Varma and D. Ray. Learning the discriminative power-invariance trade-off. In ICCV, 2007. 8