Tree-structured CRF models for interactive image labeling

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 35, Issue 2, 2013, Pages 476-489

  Mensink, Thomas ^a,b   Verbeek, Jakob ^a   Csurka, Gabriela ^b  

^a INRIA RHÔNE ALPES   (France)

^b XEROX RESEARCH CENTRE EUROPE   (France)

Author keywords

content analysis and indexing; object recognition; Pattern recognition application computer vision; pattern recognition interactive systems; statistical pattern recognition

Indexed keywords

ACCURATE PREDICTION; BENCHMARK DATASETS; CLASS PROBABILITIES; CONTENT ANALYSIS; DEPENDENCY RELATION; IMAGE LABELING; INDEPENDENT MODEL; INDEPENDENT PREDICTORS; INTERACTIVE SYSTEM; STATISTICAL PATTERN RECOGNITION; STRUCTURED MODEL; STRUCTURED PREDICTION; TEST IMAGES; TEST TIME; USER INPUT;

COMPUTER VISION; FORECASTING; OBJECT RECOGNITION;

FORESTRY;

FORECASTS; FORESTRY; IMAGE ANALYSIS; PATTERN RECOGNITION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; COMPUTER INTERFACE; DOCUMENTATION; HOSPITAL INFORMATION SYSTEM; IMAGE ENHANCEMENT; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; DOCUMENTATION; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED; RADIOLOGY INFORMATION SYSTEMS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; USER-COMPUTER INTERFACE;

MLCS; MLOWN;

EID: 84871806574     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2012.100     Document Type: Article

References (35)

1. J. Zhang, M. Marszałek, S. Lazebnik, and C. Schmid, "Local Features and Kernels for Classification of Texture and Object Categories: A Comprehensive Study, " Int'l J. Computer Vision, vol. 73, no. 2, pp. 213-238, 2007. (Pubitemid 46181625)
2. D. Grangier and S. Bengio, "A Discriminative Kernel-Based Model to Rank Images from Text Queries, " IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 30, no. 8, pp. 1371-1384, Aug. 2008.
3. M. Guillaumin, T. Mensink, J. Verbeek, and C. Schmid, "Tagprop: Discriminative Metric Learning in Nearest Neighbor Models for Image Auto-Annotation, " Proc. 12th IEEE Int'l Conf. Computer Vision, 2009.
4. M. Choi, J. Lim, A. Torralba, and A. Willsky, "Exploiting Hierarchical Context on a Large Database of Object Categories, " Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2010.
5. S. Nowak and M. Huiskes, "New Strategies for Image Annotation: Overview of the Photo Annotation Task at Imageclef 2010, " Proc. Working Notes of CLEF, 2010.
6. C. Lampert, H. Nickisch, and S. Harmeling, "Learning to Detect Unseen Object Classes by Between-Class Attribute Transfer, " Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2009.
7. S. Branson, C. Wah, F. Schroff, B. Babenko, P. Welinder, P. Perona, and S. Belongie, "Visual Recognition with Humans in the Loop, " Proc. 11th European Conf. Computer Vision, 2010.
8. T. Mensink, J. Verbeek, and G. Csurka, "Learning Structured Prediction Models for Interactive Image Labeling, " Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2011.
9. V. Vapnik, The Nature of Statistical Learning Theory. Springer, 1995.
10. F. Perronnin, J. Sánchez, and T. Mensink, "Improving the Fisher Kernel for Large-Scale Image Classification, " Proc. 11th European Conf. Computer Vision, 2010.
11. A. Makadia, V. Pavlovic, and S. Kumar, "A New Baseline for Image Annotation, " Proc. 10th European Conf. Computer Vision, 2008.
12. J. Weston, S. Bengio, and N. Usunier, "Large Scale Image Annotation: Learning to Rank with Joint Word-Image Embeddings, " Proc. European Conf. Machine Learning, 2010.
13. J. Deng, A. Berg, K. Li, and F.-F. Li, "What Does Classifying More Than 10000 Image Categories Tell Us?" Proc. 11th European Conf. Computer Vision, 2010.
14. C. Desai, D. Ramanan, and C. Fowlkes, "Discriminative Models for Multi-Class Object Layout, " Proc. IEEE Int'l Conf. Computer Vision, 2009.
15. A. Rabinovich, A. Vedaldi, C. Galleguillos, E. Wiewiora, and S. Belongie, "Objects in Context, " Proc. IEEE Int'l Conf. Computer Vision, 2007.
16. B. Settles, "Active Learning Literature Survey, " technical report, Univ. of Wisconsin-Madison, p. 1648, 2009.
17. S. Vijayanarasimhan and K. Grauman, "Multi-Level Active Prediction of Useful Image Annotations For Recognition, " Proc. Neural Information Processing System, 2009.
18. I. Tsochantaridis, T. Joachims, T. Hofmann, and Y. Altun, "Large Margin Methods for Structured and Interdependent Output Variables, " J. Machine Learning Research, vol. 6, pp. 1453-1484, 2005.
19. C. Bishop, Pattern Recognition and Machine Learning. Springer, 2006.
20. S. Nowozin and C. Lampert, "Structured Learning and Prediction in Computer Vision, " Foundations and Trends in Computer Graphics and Vision, vol. 6, pp. 185-365, 2011.
21. G. Csurka, C. Dance, L. Fan, J. Willamowski, and C. Bray, "Visual Categorization with Bags of Keypoints, " Proc. ECCV Workshop Statistical Learning in Computer Vision, 2004.
22. A. Oliva and A. Torralba, "Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope, " Int'l J. Computer Vision, vol. 42, pp. 145-175, 2001. (Pubitemid 32680801)
23. J. Bradley and C. Guestrin, "Learning Tree Conditional Random Fields, " Proc. Int'l Conf. Machine Learning, 2010.
24. C. Chow and C. Liu, "Approximating Discrete Probability Distributions with Dependence Trees, " IEEE Trans. Information Theory, vol. 14, no. 3, pp. 462-467, May 1968.
25. P. Pletscher, C. Ong, and J. Buhmann, "Spanning Tree Approximations for Conditional Random Fields, " Proc. 12th Int'l Conf. Artificial Intelligence and Statistics, 2009.
26. M. Huiskes and M. Lew, "The MIR Flickr Retrieval Evaluation, " Proc. First ACM Int'l Conf. Multimedia Information Retrieval, 2008.
27. S. Lazebnik, C. Schmid, and J. Ponce, "Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories, " Proc. IEEE Computer Vision and Pattern Recognition, 2006.
28. T. Mensink, G. Csurka, F. Perronnin, J. Sánchez, and J. Verbeek, "LEAR and XRCE's Participation to Visual Concept Detection Task-ImageCLEF 2010, " Proc. Workshop ImageCLEF, 2010.
29. M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman, "The PASCAL Visual Object Classes Challenge 2007 (VOC2007) Results, " http://www. pascal-network. org/challenges/VOC/voc2007/workshop/index. html, 2012.
30. J. Platt, "Probabilities for SV Machines, " Advances in Large Margin Classifiers, MIT Press, 2000.
31. S. Nowozin, P. Gehler, and C. Lampert, "On Parameter Learning in CRF-Based Approaches to Object Class Image Segmentation, " Proc. 11th European Conf. Computer Vision, 2010.
32. K. van de Sande and T. Gevers, "The University of Amsterdam's Concept Detection System at ImageCLEF 2010, " Proc. Workshop ImageCLEF, 2010.
33. E. Mbanya, C. Hentschel, S. Gerke, M. Liu, A. Nü rnberger, and P. Ndjiki-Nya, "Augmenting Bag-of-Words-Category Specific Features and Concept Reasoning, " Proc. Workshop ImageCLEF, 2010.
34. I. Dimitrovski, D. Kocev, S. Loskovska, and S. Dzeroski, "Detection of Visual Concepts and Annotation of Images Using Predictive Clustering Trees, " Proc. Workshop ImageCLEF, 2010.
35. N. Motohashi, R. Izawa, and T. Takagi, "Meiji University at ImageCLEF2010 Visual Concept Detection and Annotation Task, " Proc. Workshop ImageCLEF, 2010.