A revisit of generative model for automatic image annotation using markov random fields

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

Volumn , Issue , 2009, Pages 1153-1160

  Xiang, Yu ^a   Zhou, Xiangdong ^a   Chua, Tat Seng ^b   Ngo, Chong Wah ^c  

^a FUDAN UNIVERSITY   (China)

^b NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^c CITY UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; IMAGE ANALYSIS; IMAGE ANNOTATION; MAGNETORHEOLOGICAL FLUIDS; MARKOV PROCESSES; PARAMETER ESTIMATION; SEMANTIC WEB; SEMANTICS;

AUTOMATIC IMAGE ANNOTATION; AUTOMATIC IMAGE ANNOTATIONS (AIA); COMPETITIVE PERFORMANCE; MARKOV RANDOM FIELDS; OPTIMAL PARAMETER ESTIMATION; POTENTIAL FUNCTION; RECALL AND PRECISION; STATE-OF-THE-ART APPROACH;

LEARNING SYSTEMS;

EID: 70450161440     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPRW.2009.5206518     Document Type: Conference Paper

References (16)

1. L. Cao, J. Luo, H. Kautz, and T. Huang. Annotating collections of photos using hierarchical event and scene models. CVPR, 2008.
2. G. Carneiro, A. Chan, P. Moreno, and N. Vasconcelos. Supervised learning of semantic classes for image annotation and retrieval. IEEE PAMI, 29, 2007.
3. P. Duygulu, K. Barnard, J. de Freitas, and D. Forsyth. Object recognition as machine translation: learning a lexicon for a fixed image vocabulary. ECCV, 2002.
4. S. Feng, R. Manmatha, and V. Lavrenko. Multiple bernoulli relevance models for image and video annotation. CVPR, 2004.
5. J. Jeon, V. Lavrenko, and R. Manmatha. Automatic image annotation and retrieval using cross-media relevance models. SIGIR, 2003.
6. R. Jin, Y. Chai, and L. Si. Effective automatic image annotation via a coherent language model and active learning. ACM Multimedia, 2004.
7. F. Kang, R. Jin, and R. Sukthankar. Correlated label propagation with application to multi-label learning. ACM Multimedia, 2006.
8. V. Lavrenko, R. Manmatha, and J. Jeon. A model for learning the semantics of pictures. NIPS, 2004.
9. S. Z. Li. Markov random field modeling in computer vision. Springer-Verlag Press, 1995.
10. Y. Li, Y. Tsin, Y. Genc, and T. Kanade. Object detection using 2d spatial ordering contraints. CVPR, 2005.
11. J. Liu, B.Wang, M. Li, Z. Li, W. Ma, H. Lu, and S. Ma. Dual cross-media relevance model for image annotation. ACM SIGMM, 2007.
12. B. Micusik and T. Pajdla. Multi-label image segmentation via max-sum solver. CVPR, 2007.
13. G. Qi, X. Hua, Y. Rui, J. Tang, T. Mei, and H. Zhang. Correlative multi-label video annotation. ACM SIGMM, 2007.
14. C. Wang, L. Zhang, and H. Zhang. Scalable markov modelbased image annotation. CIVR, 2008.
15. C. Yang and M. Dong. Region-based image annotation using asymmetrical support vector machine-based multipleinstance learning. CVPR, 2006.
16. X. Zhou, M. Wang, J. Zhang, Q. Zhang, and B. Shi. Automatic image annotation by an iterative approach: Incorporating keyword correlations and region matching. CIVR, 2007.