Self-supervised online metric learning with low rank constraint for scene categorization

IEEE Transactions on Image Processing

Volumn 22, Issue 8, 2013, Pages 3179-3191

  Cong, Yang ^a,b   Liu, Ji ^c   Yuan, Junsong ^b   Luo, Jiebo ^d  

^a SHENYANG INSTITUTE OF AUTOMATION   (China)

^b NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^c University of Wisconsin Madison   (United States)

^d University of Rochester   (United States)

Author keywords

Low rank; metric learning; online learning; scene categorization; semi supervised learning

Indexed keywords

LOW RANK; METRIC LEARNING; ONLINE LEARNING; SCENE CATEGORIZATION; SEMI-SUPERVISED LEARNING;

CLASSIFICATION (OF INFORMATION); DATA PROCESSING; SUPERVISED LEARNING;

E-LEARNING;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; METHODOLOGY; ONLINE SYSTEM; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; PROCEDURES;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; ONLINE SYSTEMS; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBTRACTION TECHNIQUE;

EID: 84879055538     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2013.2260168     Document Type: Article

References (42)

1. H. Grabner and H. Bischof, "On-line boosting and vision," in Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit., vol. 1. Jun. 2006, pp. 260-267. (Pubitemid 44931339)
2. G. Chechik, V. Sharma, U. Shalit, and S. Bengio, "An online algorithm for large scale image similarity learning," in Advances in Neural Information Processing Systems, vol. 21. Cambridge, MA, USA: MIT Press, 2009, pp. 306-314.
3. F. Wang, C. Yuan, X. Xu, and P. van Beek, "Supervised and semi-supervised online boosting tree for industrial machine vision application," in Proc. 5th Int. Workshop Knowl. Discovery Sensor Data, 2011, pp. 43-51.
4. G. Cauwenberghs and T. Poggio, "Incremental and decremental support vector machine learning," in Advances in Neural Information Processing Systems. Cambridge, MA, USA: MIT Press, 2001, pp. 409-415.
5. B. Liu, S. Mahadevan, and J. Liu, "Regularized off-policy TD-learning," in Advances in Neural Information Processing Systems. Cambridge, MA, USA: MIT Press, 2012.
6. Y. Cong, J. Yuan, and Y. Tang, "Object tracking via online metric learning," in Proc. 19th IEEE Int. Conf. Image Process., Sep.-Oct. 2012, pp. 417-420.
7. K. van de Sande, T. Gevers, and C. Snoek, "Evaluating color descriptors for object and scene recognition," IEEE Trans. Pattern Anal. Mach. Intell., vol. 32, no. 9, pp. 1582-1596, Sep. 2010.
8. M. Szummer and R. Picard, "Indoor-outdoor image classification, " in Proc. IEEE Int. Workshop Content-Based Access Image Video Database, Jan. 1998, pp. 42-51.
9. D. Lowe, "Distinctive image features from scale-invariant keypoints," Int. J. Comput. Vis., vol. 60, no. 2, pp. 91-110, 2004.
10. A. Oliva and A. Torralba, "Modeling the shape of the scene: A holistic representation of the spatial envelope," Int. J. Comput. Vis., vol. 42, no. 3, pp. 145-175, 2001. (Pubitemid 32680801)
11. S. Lazebnik, C. Schmid, and J. Ponce, "Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories," in Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit., vol. 2. 2006, pp. 2169-2178. (Pubitemid 44931582)
12. J. van Gemert, J. Geusebroek, C. Veenman, and A. Smeulders, "Kernel codebooks for scene categorization," in Proc. 10th Eur. Conf. Comput. Vis., 2008, pp. 696-709.
13. A. Quattoni and A. Torralba, "Recognizing indoor scenes," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jun. 2009, pp. 413-420.
14. J. Wu, H. Christensen, and J. Rehg, "Visual place categorization: Problem, dataset, and algorithm," in Proc. IEEE/RSJ Int. Conf. Intell. Robots Syst., Oct. 2009, pp. 4763-4770.
15. J. Wu and J. Rehg, "CENTRIST: A visual descriptor for scene categorization," IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, no. 8, pp. 1489-1501, Aug. 2011.
16. Y. Cong, J. Yuan, and J. Luo, "Toward scalable summarization of consumer videos via sparse dictionary selection," IEEE Trans. Multimedia, vol. 14, no. 1, pp. 66-75, Feb. 2012.
17. L. Li and L. Fei-Fei, "What, where and who? Classifying events by scene and object recognition," in Proc. IEEE 11th Int. Conf. Comput. Vis., vol. 2. Oct. 2007, pp. 1-8.
18. D. Walther, E. Caddigan, L. Fei-Fei, and D. Beck, "Natural scene categories revealed in distributed patterns of activity in the human brain," J. Neurosci., vol. 29, no. 34, pp. 10573-10581, 2009.
19. L. Li, R. Socher, and L. Fei-Fei, "Toward total scene understanding: Classification, annotation and segmentation in an automatic framework," in Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit., Jun. 2009, pp. 2036-2043.
20. J. Liu and M. Shah, "Scene modeling using co-clustering," in Proc. IEEE 11th Int. Conf. Comput. Vis., Oct. 2007, pp. 1-7.
21. P. Quelhas, F. Monay, J. Odobez, D. Gatica-Perez, and T. Tuytelaars, "A thousand words in a scene," IEEE Trans. Pattern Anal. Mach. Intell., vol. 29, no. 9, pp. 1575-1589, Sep. 2007. (Pubitemid 47299912)
22. A. Bosch, A. Zisserman, and X. Muoz, "Scene classification using a hybrid generative/discriminative approach," IEEE Trans. Pattern Anal. Mach. Intell., vol. 30, no. 4, pp. 712-727, Apr. 2008. (Pubitemid 351559723)
23. J. Kivinen, E. Sudderth, and M. Jordan, "Learning multiscale representations of natural scenes using Dirichlet processes," in Proc. IEEE 11th Int. Conf. Comput. Vis., Oct. 2007, pp. 1-8.
24. J. Vogel and B. Schiele, "Semantic modeling of natural scenes for content-based image retrieval," Int. J. Comput. Vis., vol. 72, no. 2, pp. 133-157, 2007. (Pubitemid 46094757)
25. P. Utgoff, N. Berkman, and J. Clouse, "Decision tree induction based on efficient tree restructuring," Mach. Learn., vol. 29, no. 1, pp. 5-44, 1997. (Pubitemid 127507172)
26. S. Avidan, "Ensemble tracking," in Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit., vol. 2. Jun. 2005, pp. 494-501.
27. X. Liu and T. Yu, "Gradient feature selection for online boosting," in Proc. IEEE 11th Int. Conf. Comput. Vis., Oct. 2007, pp. 1-8.
28. N. Oza and S. Russell, "Online bagging and boosting," in Proc. Artif. Intell. Stat., 2001, pp. 105-112.
29. E. Lughofer, "On-line evolving image classifiers and their application to surface inspection," Image Vis. Comput., vol. 28, no. 7, pp. 1065-1079, 2010.
30. F. Gayubo, J. Gonzalez, E. de la Fuente, F. Miguel, and J. Peran, "Online machine vision system for detect split defects in sheet-metal forming processes," in Proc. 18th Int. Conf. Pattern Recognit., vol. 1. 2006, pp. 723-726. (Pubitemid 46532004)
31. O. Camoglu, T. Yu, L. Bertelli, D. Vu, V. Muralidharan, and S. Gokturk, "An efficient fashion-driven learning approach to model user preferences in on-line shopping scenarios," in Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit. Workshops, Jun. 2010, pp. 28-34.
32. K. Weinberger and L. Saul, "Distance metric learning for large margin nearest neighbor classification," J. Mach. Learn. Res., vol. 10, pp. 207-244, Feb. 2009.
33. P. Jain, B. Kulis, I. Dhillon, and K. Grauman, "Online metric learning and fast similarity search," in Advances in Neural Information Processing Systems. Cambridge, MA, USA: MIT Press, 2008, pp. 761-768.
34. A. Globerson and S. Roweis, "Metric learning by collapsing classes," in Advances in Neural Information Processing Systems. Cambridge, MA, USA: MIT Press, 2006.
35. K. Crammer, O. Dekel, J. Keshet, S. Shalev-Shwartz, and Y. Singer, "Online passive-aggressive algorithms," J. Mach. Learn. Res., vol. 7, pp. 551-585, Mar. 2006. (Pubitemid 43668115)
36. G. Chechik, V. Sharma, U. Shalit, and S. Bengio, "Large scale online learning of image similarity through ranking," J. Mach. Learn. Res., vol. 11, no. 3, pp. 1109-1135, 2010.
37. H. Cheng, Z. Liu, and J. Yang, "Sparsity induced similarity measure for label propagation," in Proc. 12th IEEE Int. Conf. Comput. Vis., Sep.-Oct. 2009, pp. 317-324.
38. K. Weinberger, J. Blitzer, and L. Saul, "Distance metric learning for large margin nearest neighbor classification," in Advances in Neural Information Processing Systems. Cambridge, MA, USA: MIT Press, 2006.
39. (2009). Visual Place Categorization (VPC '09) [Online]. Available: http://categorizingplaces.com/dataset.html
40. G. Griffin, A. Holub, and P. Perona, "Caltech-256 object category dataset," California Inst. Technol., Pasadena, CA, USA, Tech. Rep. CNS-TR-2007-001, 2007.
41. N. Jacobson, Y. Freund, and T. Nguyen, "An online learning approach to occlusion boundary detection," IEEE Trans. Image Process., vol. 21, no. 1, pp. 252-261, Jan. 2012.
42. Y. Wu, J. Cheng, J. Wang, H. Lu, J. Wang, H. Ling, E. Blasch, and L. Bai, "Real-time probabilistic covariance tracking with efficient model update," IEEE Trans. Image Process., vol. 21, no. 5, pp. 2824-2837, May 2012.