An energy-based model for region-labeling

Computer Vision and Image Understanding

Volumn 115, Issue 6, 2011, Pages 787-803

  Escalante, Hugo Jair ^a   Montes Y Goméz, Manuel ^b   Sucar, Luis Enrique ^b  

^a UNIVERSIDAD AUTÓNOMA DE NUEVO LEÓN   (Mexico)

^b INSTITUTO NACIONAL DE ASTROFÍSICA   (Mexico)

Author keywords

Energy based modeling; Image annotation; Object recognition; Random forest; Region labeling

Indexed keywords

BASE CLASSIFIERS; DATA SETS; ENERGY-BASED MODELING; ENERGY-BASED MODELS; HETEROGENEOUS DATA; IMAGE ANNOTATION; MULTICLASS CLASSIFICATION METHODS; RANDOM FORESTS; REFINEMENT TECHNIQUES; REGION LABELING;

DECISION TREES; IMAGE ANALYSIS; IMAGE RETRIEVAL; SEMANTICS;

OBJECT RECOGNITION;

EID: 79952351372     PISSN: 10773142     EISSN: 1090235X     Source Type: Journal    
DOI: 10.1016/j.cviu.2011.02.002     Document Type: Article

References (46)

1. K. Barnard, P. Duygulu, N. de Freitas, D.A. Forsyth, D. Blei, and M.I. Jordan Matching words and pictures Journal of Machine Learning Research 3 2003 1107 1135
2. R. Datta, D. Joshi, J. Li, and J.Z. Wang Image retrieval: ideas, influences, and trends of the new age ACM Computing Surveys 40 2 2008 1 60
3. H.J. Escalante, M. Montes, L.E. Sucar, Multimedia document indexing based on semantic cohesion, Information Retrieval, 2011, accepted for publication.
4. H.J. Escalante, M. Grubinger, C.A. Hernández, J.A. González, A. López, M. Montes, E. Morales, L.E. Sucar, and L. Villaseñor The segmented and annotated IAPR TC-12 benchmark Computer Vision and Image Understanding 114 2010 419 428
5. M. Inoue, On the need for annotation-based image retrieval, in: Proceedings of the ACM-SIGIR Workshop on Information Retrieval in Context, Sheffield, UK, 2004, pp. 44-46.
6. J. Jeon, V. Lavrenko, R. Manmatha. Automatic image annotation and retrieval using cross-media relevance models, in: SIGIR'03: Proceedings of the 26th International ACM-SIGIR Conference on Research and Development on Information Retrieval, Toronto, Canada, 2003, pp. 119-126.
7. A. Hanbury A survey of methods for image annotation Journal of Visual Languages and Computing 19 5 2008 617 627
8. K. Barnard, Q. Fan, R. Swaminathan, A. Hoogs, R. Collins, P. Rondot, and J. Kaufhold Evaluation of localized semantics: data, methodology, and experiments International Journal of Computer Vision 77 1-3 2008 199 217 (Pubitemid 351294742)
9. H.J. Escalante, M. Montes, L.E. Sucar, Word co-occurrence and Markov random fields for improving automatic image annotation, in: Proceedings of the 18th British Machine Vision Conference, vol. 2, Warwick, UK, 2007, pp. 600-609.
10. G. Papadopoulos, V. Mezaris, I. Kompatsiaris, M. Strintzis, Combining global and local information for knowledge-assisted image analysis and classification, EURASIP Journal on Advances in Signal Processing 2007, 2007, p. 15 (Article ID 45842).
11. C. Galleguillos, A. Rabinovich, S. Belongie, Object categorization using co-occurrence, location and appearance, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Anchorage, Alaska, 2008, pp. 1-8.
12. C. Saathoff, M. Grzegorzek, and S. Staab Labeling image regions using wavelet features and spatial prototypes Proceedings of the 3rd International Conference on Semantic and Digital Media Technologies: Semantic Multimedia, LNCS vol. 5392 2008 Springer Koblenz, Germany 89 104
13. C. Saathoff, and S. Staab Exploiting spatial context in image region labelling using fuzzy constraint reasoning Proceedings of the 9th International Workshop on Image Analysis for Multimedia Interactive Services 2008 IEEE Klagenfurt, Austria 16 19
14. G. Papadopoulos, C. Saathoff, M. Grzegorzek, V. Mezaris, I. Kompatsiaris, S. Staab, and M. Strintzis Comparative evaluation of spatial context techniques for semantic image analysis Proceedings of the 10th International Workshop on Image Analysis for Multimedia Interactive Services 2009 IEEE London, UK 161 164
15. C. Hernandez, and L.E. Sucar Markov random fields and spatial information to improve automatic image annotation Proceedings of the 2007 Pacific-Rim Symposium on Image and Video Technology, LNCS vol. 4872 2007 Springer Santiago, Chile 879 892
16. H.J. Escalante, M. Montes, L.E. Sucar, Multi-class PSMS for automatic image annotation. Swarm Intelligence Journal, 2011.
17. J. Vogel, and B. Shiele Semantic modeling of natural scenes for content-based image retrieval International Journal on Computer Vision 72 2 2007 133 157 (Pubitemid 46094757)
18. J. Winn, A. Criminisi, T. Minka, Object categorization by learned universal visual dictionary, in: Proceedings of IEEE International Conference on Computer Vision, Beijing, China, 2005, pp. 1800-1807. (Pubitemid 44042395)
19. J. Shotton, J. Winn, C. Rother, and A. Criminisi Textonboost for image understanding: multi-class object recognition and segmentation by jointly modeling appearance, shape and context International Journal on Computer Vision 81 1 2008 2 24
20. A. Llorente, R. Manmatha, S. Rüger, Image retrieval using Markov random fields and global image features, in: Proceedings of the ACM International Conference on Image and Video Retrieval, Xian, China, 2010, pp. 243-250.
21. Y. Jiang, J. Wang, S. Chang, C. Ngo, Domain adaptive semantic diffusion for large scale context-based video annotation, in: Proceedings of IEEE International Conference on Computer Vision, Kyoto, Japan, 2009, pp. 1420-1427.
22. Y.J. Lee, K. Grauman, Object-graphs for context-aware category discovery, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, San Francisco, CA, USA, 2010, pp. 1-8.
23. A. Llorente, S. Overell, H. Liu, R. Hu, A. Rae, J. Zhu, D. Song, and S. Rüger Exploiting term co-occurrence for enhancing automated image annotation Evaluating Systems for Multilingual and Multimodal Information Access - 9th Workshop of the CLEF, LNCS vol. 5706 2009 Springer 632 639
24. B. Yao, L. Fei-Fei, Modeling mutual context of object and human pose in human-object interaction activities, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, San Francisco, CA, USA, 2010, pp. 17-24.
25. R. Rifkin, and A. Klautau In defense of one-vs-all classification Journal of Machine Learning Research 5 2004 101 141
26. W. Li, M. Sun, Semi-supervised learning for image annotation based on conditional random fields, in: Proceedings of the International Conference on Image and Video Retrieval, LNCS, vol. 4071, Tempe, AZ, USA, 2006, pp. 463-472. (Pubitemid 44153585)
27. J. Yuan, J. Li, B. Zhang, Exploiting spatial context constraints for automatic image region annotation, in: Proceedings of the 15th ACM International Conference on Multimedia, Augsburg, Germany, 2007, pp. 595-604.
28. T. Hastie, R. Tibshirani, and J. Friedman The Elements of Statistical Learning: Data Mining, Inference, and Prediction 2001 Springer
29. P. Carbonetto, N. de Freitas, and K. Barnard A statistical model for general context object recognition Proceedings of the 8th European Conference on Computer Vision LNCS vol. 3021 2004 Springer Prague, Czech Republic 350 362
30. Y. LeCun, S. Chopra, R. Hadsell, M.A. Ranzato, and F.J. Huang Energy-based models Predicting Structured Data 2007 MIT Press 191 246 (Chapter 10)
31. G. Winkler Image Analysis Random Fields and Markov Chain Monte Carlo Methods Number 27 in Applications of Mathematics 2006 Springer
32. J. Besag On the statistical analysis of dirty pictures Journal of the Royal Statistical Society, Series B 48 1986 259 302
33. S. Kirkpatrick, C. Gelatt, and M. Vecchi Optimization by simulated annealing Science 220 4598 1983 671 680
34. Yuri Boykov, Olga Veksler, and Ramin Zabih Efficient approximate energy minimization via graph cuts IEEE Transactions on Pattern Analysis and Machine Intelligence 20 12 2001 1222 1239 (Pubitemid 33137959)
35. M. Grubinger, Analysis and Evaluation of Visual Information Systems Performance, PhD Thesis. School of Computer Science and Mathematics, Faculty of Health, Engineering and Science, Victoria University, Melbourne, Australia, 2007.
36. J. Shi, and J. Malik Normalized cuts and image segmentation IEEE Transactions on Pattern Analysis and Machine Intelligence 22 8 2000 888 905
37. V. Mezaris, I. Kompatsiaris, and M. Strintzis Still image segmentation tools for object-based multimedia applications International Journal of Pattern Recognition and Artificial Intelligence 18 2004 701 726
38. A. Saffari, I. Guyon. Quickstart Guide for CLOP, Tech. Rep., Graz University of Technology and Clopinet, Graz, Austria, 2006.
39. H.J. Escalante, M. Montes, and L.E. Sucar Particle swarm model selection Journal of Machine Learning Research 10 2009 405 440
40. L. Breiman Random forest Machine Learning 45 1 2001 5 32
41. C. Dahinden, Classification with tree-based ensembles applied to the WCCI 2006 performance prediction challenge datasets, in: Proceedings of the International Joint Conference on Neural Networks, Vancouver, BC, Canada, 2006, pp. 1669-1672. (Pubitemid 351369523)
42. S. Dudoit, and J. Fridlyand Classification in Microarray Experiments, Chapter in Statistical Analysis of Gene Microarraty Data 2002 CRC Press
43. I. Guyon, A. Saffari, G. Dror, and Gavin Cawley Analysis of the IJCNN 2007 competition agnostic learning vs. prior knowledge Neural Networks 21 2-3 2008 544 550
44. J. Demsar Statistical comparisons of classifiers over multiple data sets Journal of Machine Learning Research 7 2006 1 30 (Pubitemid 43022939)
45. G.Th. Papadopoulos, C. Saathoff, H.J. Escalante, V. Mezaris, I. Kompatsiaris, M.G. Strintzis. A comparative study of spatial context techniques for semantic image analysis, Computer Vision and Image Understanding, submitted for publication.
46. A. Makadia, V. Pavlovi, and S. Kumar A new baseline for image annotation Proceedings of the 10th European Conference on Computer Vision LNCS vol. 5304 2008 Springer Marseille, France 316 329