Markov random fields and spatial information to improve automatic image annotation

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

Volumn 4872 LNCS, Issue , 2007, Pages 879-892

  Hernández Gracidas, Carlos ^a   Sucar, L Enrique ^a  

^a INSTITUTO NACIONAL DE ASTROFÍSICA   (Mexico)

Author keywords

Automatic image annotation; Content based image retrieval; Markov random fields; Spatial relations

Indexed keywords

FEATURE EXTRACTION; INFORMATION ANALYSIS; MARKOV PROCESSES; PROBABILISTIC LOGICS;

AUTOMATIC IMAGE ANNOTATION; CONTENT-BASED IMAGE RETRIEVAL (CBIR);

IMAGE RETRIEVAL;

EID: 38149044847     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-77129-6_74     Document Type: Conference Paper

References (18)

1. Shi, J., Malik, J.: Normalized cuts and image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence 22, 888-905 (2000)
2. Preston, C.: Gibbs States on Countable Sets. Cambridge University Press, Cambridge (1974)
3. Spitzer, F.: Random Fields and Interacting Particle Systems. Mathematical Association of America (1971)
4. Allen, J.F.: Maintaining knowledge about temporal intervals. Communications of the ACM 26(11), 832-843 (1983)
5. Egenhofer, M., Sharma, J., Mark, D.: A critical comparison of the 4-intersection and 9-intersection models for spatial relations: Formal analysis. In: R.B., M., M., A. (eds.) Eleventh International Symposium on Computer-Assisted Cartography, Auto-Carto 11, Minneapolis, Minnesota, USA, pp. 1-11 (1993)
6. Chen, J., Li, Z., Li, C., Gold, C.: Describing topological relations with voronoibased 9-intersection model. International Archives of Photogrammetry and Remote Sensing 32(4), 99-104 (1998)
7. Sistla, A., Yu, C., Haddack, R.: Reasoning about spatial relationships in picture retrieval systems. In: Bocea, J., Jarke, M., Zaniolo, C. (eds.) VLDB 1994. Twentieth International Conference on Very Large Data Bases, Santiago, Chile, pp. 570-581 (1994)
8. Zhang, Q., Yau, S.: On intractability of spatial relationships in content-based image database systems. Communications in Information and Systems 4(2), 181-190 (2004)
9. Zhang, Q., Chang, S., Yau, S.: On consistency checking of spatial relationships in content-based image database systems. Communications in Information and Systems 5(3), 341-366 (2005)
10. Hollink, L., Nguyen, G., Schreiber, G., Wielemaker, J., Wielinga, B., Worring, M.: Adding spatial semantics to image annotations. In: SemAnnot 2004. Fourth International Workshop on Knowledge Markup and Semantic Annotation, Hiroshima, Japan. LNCS, Springer, Heidelberg (2004)
11. Rathi, V., Majumdar, A.: Content based image search over the world wide web. In: Chaudhuri, S., Zisserman, A., Jain, A., Majumder, K. (eds.) ICVGIP 2002. Third Indian Conference on Computer Vision, Graphics and Image Processing, Ahmadabad, India (2002)
12. Ren, W., Singh, M., Singh, S.: Image retrieval using spatial context. In: Wellstead, P. (ed.) IWSSIP 2002. Ninth International Workshop on Systems, Signals and Image Processing, Manchester, UK, vol. 18, pp. 44-49 (2002)
13. Neapolitan, R.: Probabilistic Reasoning in Expert Systems. Wiley, New York (1990)
14. Kirkpatrick, S., Gelatt, C., Vecchi, M.: Optimization by simulated annealing. Science 220(4598), 671-680 (1983)
15. Carbonetto, P.: Unsupervised statistical models for general object recognition. Msc thesis, The Faculty of Graduate Studies, Department of Computer Science, The University of British Columbia, West Mall Vancouver, BC Canada (2003)
16. Escalante, H., Montes, M., Sucar, L.: Word co-occurrence and markov random fields for improving automatic image annotation. In: Rajpoot, N.M., B.A. (eds.) BMVC 2007. Eighteenth British Machine Vision Conference, Warwick, UK, vol. 2, pp. 600-609 (2007)
17. Back, T.: Evolutionary Algorithms in Theory and Practice: Evolution Strategies, Evolutionary Programming, Genetic Algorithms. Oxford Univ. Press, Oxford (1996)
18. Wellington, C., Courville, A., Stentz, A.: Interacting markov random fields for simultaneous terrain modeling and obstacle detection. In: Thrun, S., Sukhatme, G., Schaal, S. (eds.) RSS 2005. Robotics: Science and Systems, Boston, USA, pp. 1-8 (2005)