Human reidentification with transferred metric learning

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

Volumn 7724 LNCS, Issue PART 1, 2013, Pages 31-44

  Li, Wei ^a   Zhao, Rui ^a   Wang, Xiaogang ^a  

^a CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

[No Author keywords available]

Indexed keywords

LEARNING PROCESS; METRIC LEARNING; NON-OVERLAPPING CAMERA VIEWS; RE IDENTIFICATIONS; TEMPORAL REASONING; TRAINING SAMPLE; TRANSFER LEARNING; VISUAL SIMILARITY;

ARTIFICIAL INTELLIGENCE;

LEARNING SYSTEMS;

EID: 84875891971     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-37331-2_3     Document Type: Conference Paper

References (38)

1. Gheissari, N., Sebastian, T.B., Rittscher, J., Hartley, R.: Person reidentification using spatiotemporal appearance. In: CVPR (2006)
2. Schwartz, W., Davis, L.: Learning discriminative appearance-based models using partial least sqaures. In: Proc. XXII SIBGRAPI (2009)
3. Farenzena, M., Bazzani, L., Perina, A., Murino, V., Cristani, M.: Person re-identification by symmetry-driven accumulation of local features. In: CVPR (2010)
4. Zheng, W., Gong, S., Xiang, T.: Person re-identification by probabilistic relative distance comparison. In: CVPR (2011)
5. Park, U., Jain, A., Kitahara, I., Kogure, K., Hagita, N.: Vise: Visual search engine using multiple networked cameras. In: ICPR (2006)
6. van de Weijer, J., Schmid, C.: Coloring Local Feature Extraction. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006, Part II. LNCS, vol. 3952, pp. 334-348. Springer, Heidelberg (2006)
7. Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: CVPR (2005)
8. Wang, X., Doretto, G., Sebastian, T., Rittscher, J., Tu, P.: Shape and appearance context modeling. In: ICCV (2007)
9. Daugman, J.G.: Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters. Journal of the Optical Society of America A 2, 1160-1169 (1985)
10. Ojala, T., Pietikäinen, M., Mäenpää, T.: Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Trans. on PAMI, 971-987 (2002)
11. Torralba, A., Murphy, K., Freeman, W., Rubin, M.: Context-based vision system for place and object recognition. In: ICCV (2003)
12. Porikli, F.: Inter-camera color calibration by correlation model function. In: ICIP (2003)
13. Javed, O., Shafique, K., Shah, M.: Appearance modeling for tracking in multiple non-overlapping cameras. In: CVPR (2005)
14. Gilbert, A., Bowden, R.: Tracking Objects Across Cameras by Incrementally Learning Inter-camera Colour Calibration and Patterns of Activity. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006, Part II. LNCS, vol. 3952, pp. 125-136. Springer, Heidelberg (2006) (Pubitemid 44029722)
15. Prosser, B., Gong, S., Xiang, T.: Multi-camera matching using bi-directional cumulative brightness transfer function. In: BMVC (2008)
16. Gray, D., Tao, H.: Viewpoint Invariant Pedestrian Recognition with an Ensemble of Localized Features. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part I. LNCS, vol. 5302, pp. 262-275. Springer, Heidelberg (2008)
17. Shan, Y., Sawhney, H.S., Kumar, R.: Unsupervised Learning of Discriminative Edge Measures for Vehicle Matching between Nonoverlapping Cameras. IEEE Transactions on Pattern Analysis and Machine Intelligence 30, 700-711 (2008)
18. Lin, Z., Davis, L.S.: Learning Pairwise Dissimilarity Profiles for Appearance Recognition in Visual Surveillance. In: Bebis, G., Boyle, R., Parvin, B., Koracin, D., Remagnino, P., Porikli, F., Peters, J., Klosowski, J., Arns, L., Chun, Y.K., Rhyne, T.-M., Monroe, L. (eds.) ISVC 2008, Part I. LNCS, vol. 5358, pp. 23-34. Springer, Heidelberg (2008)
19. Prosser, B., Zheng, W., Gong, S., Xiang, T., Mary, Q.: Person re-identification by support vector ranking. In: BMVC (2010)
20. Tsochantaridis, I., Joachims, T., Hofmann, T., Altun, Y.: Large margin methods for structured and interdependent output variables. Journal of Machine Learning Research 6, 1453-1484 (2005)
21. Gray, D., Brennan, S., Tao, H.: Evaluating appearance models for recognition, reacquisition and tracking (2007)
22. Dai, W., Yang, Q., Xue, G., Yu, Y.: Boosting for transfer learning. In: Proc. of ICML (2007)
23. Wu, X., Srihari, R.: Incorporating prior knowledge with weighted margin support vector machines. In: Proc. of SIGKDD (2004)
24. Jiang, W., Zavesky, E., Chang, S., Loui, A.: Cross-domain learning methods for high-level visual concept classification. In: ICIP (2008)
25. Saenko, K., Kulis, B., Fritz, M., Darrell, T.: Adapting Visual Category Models to New Domains. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part IV. LNCS, vol. 6314, pp. 213-226. Springer, Heidelberg (2010)
26. Yao, Y., Doretto, G.: Boosting for transfer learning with multiple sources. In: CVPR (2010)
27. Qi, G., Aggarwal, C., Huang, T.: Towards semantic knowledge propagation from text corpus to web images. In: Proc. of WWW (2011)
28. Yang, J., Yan, R., Hauptmann, A.G.: Cross-domain video concept detection using adaptive svms. In: Proc. of ACM Multimedia (2007)
29. Duan, L., Tsang, I.W., Xu, D., Maybank, S.J.: Domain transfer svm for video concept detection. In: CVPR (2009)
30. Qi, G., Aggarwal, C., Rui, Y., Tian, Q., Chang, S., Huang, T.: Towards cross-category knowledge propagation for learning visual concepts. In: CVPR (2011)
31. Zhan, D.C., Li, M., Li, Y.F., Zhou, Z.H.: Learning instance specific distances using metric propagation. In: Proc. of ICML, p. 154 (2009)
32. Sande, K., Gevers, T., Snoek, C.G.M.: Evaluating color descriptors for object and scene recognition. IEEE Trans. on PAMI 32, 1582-1596 (2010)
33. Liu, T., Moore, A.W., Gray, A.G., Yang, K.: An investigation of practical approximate nearest neighbor algorithms. In: Proc. of NIPS (2004)
34. Fletcher, R.: Semi-definite matrix constraints in optimization. SIAM J. Control Optim. 23, 493-513 (1985)
35. Weinberger, K.Q., Saul, L.K.: Distance metric learning for large margin distance metric learning for large margin. Journal of Machine Learning Research 10, 207-244 (2009)
36. Luenberger, D.G., Ye, Y.: Linear and Nonlinear Programming. Springer (2008)
37. Boyd, S., Parikh, N., Chu, E., Peleato, B., Eckstein, J.: Distributed optimization and statistical learning via the alternating direction method of multipliers. Foundations and Trends in Machine Learning 3, 1-122 (2011)
38. Davis, J.V., Kulis, B., Jain, P., Sra, S., Dhillon, I.S.: Information-theoretic metric learning. In: Proc. of ICML (2007)