Scene parsing using region-based generative models

IEEE Transactions on Multimedia

Volumn 9, Issue 1, 2007, Pages 136-146

  Boutell, Matthew R ^a,b   Luo, Jiebo ^a,c   Brown, Christopher M ^d  

^a IEEE   (United States)

^b ROSE HULMAN INSTITUTE OF TECHNOLOGY   (United States)

^c EASTMAN KODAK COMPANY   (United States)

^d University of Rochester   (United States)

Author keywords

Factor graph; Generative models; Scene classification; Semantic features

Indexed keywords

FACTOR GRAPHS; SCENE CONFIGURATION MODELS; SEMANTIC OBJECT DETECTORS; SEMANTIC SCENE CLASSIFICATION;

CLASSIFICATION (OF INFORMATION); COMPUTER VISION; FEATURE EXTRACTION; GRAPH THEORY; OBJECT RECOGNITION; PROBABILITY; PROBLEM SOLVING;

SEMANTICS;

EID: 33846227017     PISSN: 15209210     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMM.2006.886372     Document Type: Article

References (22)

1. M. Boutell, J. Luo, and C. M. Brown, "Learning spatial configuration models using modified Dirichlet priors," in Proc. Workshop on Statistical Relational Learning (in Conjunction With ICML), 2004.
2. _, "Improved semantic region labeling based on scene context," in Proc. Int. Conf. Multimedia and Expo., Amsterdam, The Netherlands, Jul. 2005.
3. M. Boutell, A. Choudhury, J. Luo, and C. M. Brown, "Using semantic features for scene classification: How good do they need to be?," in Proc. IEEE Int. Conf. Multimedia and Expo., Jul. 2006.
4. B. Bradshaw, J. Platt, and B. Scholkopf, Kernel Methods for Extracting Local Image Semantics 2001, Microsoft Research Technical Report MSR-TR-2001-99.
5. P. Chou, The Theory and Practice of Bayesian Image Labeling. Rochester, NY, Univ. Rochester, 1988, Ph.D. dissertation.
6. D. Comaniciu and P. Meer, "Mean shift: A robust approach toward feature space analysis," IEEE Trans. Pattern Anal. Mach. Intell., vol. 24, no. 5, pp. 603-619, May 2002.
7. J. Fan, H. Luo, and Y. Gao, "Learning the semantics of images by using unlabeled samples," in Proc. IEEE Conf. Computer Vision and Pattern Recognition, Jun. 2005.
8. W. Freeman, E. Pasztor, and O. Carmichael, "Learning low-level vision," Int. J. Comput. Vis., vol. 40, no. 1, pp. 24-57, Oct. 2000.
9. S. Geman and D. Geman, "Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images," IEEE Trans. Pattern Anal. Mach. Intell., vol. PAMI-6, no. 6, pp. 721-741, Nov. 1984.
10. F. R. Kschischang, B. H. Frey, and H.-A. Loeliger, "Factor graphs and the sum-product algorithm," IEEE Trans. Inform. Theory, vol. 47, no. 2. pp. 498-519, Feb. 2001.
11. J. Luo and S. P. Etz, "A physical model-based approach to detecting sky in photographic images," IEEE Trans. Image Process., vol. 11, no. 3. pp. 201-212, Mar. 2002.
12. P. Mulhem, W. K. Leow, and Y. K. Lee, "Fuzzy conceptual graphs for matching images of natural scenes," in Proc. Int. Joint Conf. Artificial Intelligence, 2001, pp. 1397-1404.
13. M. R. Naphade and T. S. Huang, "A probabilistic framework for semantic video indexing, filtering, and retrieval," IEEE Trans. Multimedia, vol. 3, no. 1, pp. 141-151, Mar. 2001.
14. J. Pearl, Ed., Probabilistic Reasoning in Intelligent Systems. San Mateo, CA: Morgan Kaufmann, 1988.
15. A. Singhal, J. Luo, and W. Zhu, "Probabilistic spatial context models for scene content understanding," in Proc. IEEE Conf. Computer Vision and Pattern Recognition, Madison, WI, Jun. 2003.
16. J. R. Smith and C.-S. Li, "Image classification and querying using composite region templates," Comput. Vis. Image Understand., vol. 75, no. 1/2, pp. 165-174, 1999.
17. J. Smith, C. Lin, M. Naphade, A. Natsev, and B. Tseng, "Multimedia semantic indexing using model vectors," in Proc. IEEE Int. Conf. Multimedia & Expo., Baltimore, MD, 2003.
18. A. Torralba, K. P. Murphy, and W. T. Freeman, "Sharing features: Efficient boosting procedures for multiclass object detection," in Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2004, pp. 762-769.
19. A. Vailaya, M. Figueiredo, A. Jain, and H.-J. Zhang, "Content-based hierarchical classification of vacation images," in Proc. IEEE Multimedia Systems '99, Florence, Italy, 1999.
20. A. Vailaya and A. Jain, "Detecting sky and vegetation in outdoor images," in Proc. SPIE, 2000, vol. 3972, pp. 411-420.
21. N. Vapnik, The Nature of Statistical Learning Theory. New York: Springer, 1995.
22. Y. Wang and H.-J. Zhang, "Detecting image orientation based on low-level visual content," Comput. Vis. Image Understand., vol. 93, no. 3, pp. 328-346, 2004.