Learning globally-consistent local distance functions for shape-based image retrieval and classification

Proceedings of the IEEE International Conference on Computer Vision

Volumn , Issue , 2007, Pages

  Frome, Andrea ^a   Sha, Fei ^a   Singer, Yoram ^b   Malik, Jitendra ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b GOOGLE INC   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DISTANCE FUNCTIONS;

ARTIFICIAL INTELLIGENCE; CLASSIFICATION (OF INFORMATION); COMPUTER NETWORKS; COMPUTER VISION; HEURISTIC PROGRAMMING; IMAGE ENHANCEMENT; IMAGE PROCESSING; IMAGE RETRIEVAL; LEARNING SYSTEMS; OBJECT RECOGNITION;

LEARNING ALGORITHMS;

EID: 50649117726     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2007.4408839     Document Type: Conference Paper

References (25)

1. A. Berg, T. Berg, and J. Malik. Shape matching and object recognition using low distortion correspondence. In CVPR, 2005.
2. A. Berg and J. Malik. Geometric blur for template matching. In CVPR, pages 607-614, 2001.
3. K. Crammer, O. Dekel, J. Keshet, S. Shalev-Shwartz, and Y. Singer. Online passive aggressive algorithms. Journal of Machine Learning Research, 7, Mar 2006.
4. L. Fei-Fei, R. Fergus, and P. Perona. Learning generative visual models from few training examples: an incremental bayesian approach testing on 101 object categories. In Workshop on Generative-Model Based Vision, CVPR, 2004.
5. A. Frome. Learning Distance Functions for Exemplar-Based Object Recognition. PhD thesis, UC Berkeley, 2007.
6. A. Frome, Y. Singer, and J. Malik. Image retrieval and classification using local distance functions. In NIPS, 2006.
7. A. Globerson and S. Roweis. Metric learning by collapsing classes. In NIPS, 2005.
8. K. Grauman and T. Darrell. Approximate correspondences in high dimensions. In NIPS, 2006.
9. K. Grauman and T. Darrell. Pyramic match kernels: Discriminative classficiation with sets of image features (version 2). Technical Report MIT_CSAIL_TR_2006-020, MIT, March 2006.
10. G. Griffin, A. Holub, and P. Perona. Caltech-256 object category dataset. Technical Report UCB/CSD-04-1366, California Institute of Technology, 2007.
11. A. D. Holub, M. Welling, and P. Perona. Combining generative models and fisher kernels for object recognition. In ICCV, 2005.
12. M. Kearns and D. Ron. Algorithmic stability and sanity-check bounds for leave-one-out cross-validation. Neural Computation, 11:1427-1453, 1999.
13. S. Lazebnik, C. Schmid, and J. Ponce. Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories. In CVPR, 2006.
14. D. Lowe. Object recognition from local scale-invariant features. In ICCV, pages 1000-1015, Sep 1999.
15. D. Martin, C. Fowlkes, and J. Malik. Learning to detect natural image boundaries using local brightness, color and texture cues. TPAMI, 26(5):530-549, May 2004.
16. J. Mutch and D. G. Lowe. Multiclass object recognition with sparse, localized features. In CVPR, 2006.
17. J. Platt. Advances in Kernel Methods - Support Vector Learning, chapter Fast Training of Support Vector Machines using Sequential Minimal Optimization, pages 185-208. MIT Press, 1998.
18. M. Schutlz and T. Joachims. Learning a distance metric from relative comparisons. In NIPS, 2003.
19. T. Serre, L. Wolf, and T. Poggio. Object recognition with features inspired by visual cortex. In CVPR, 2005.
20. S. Shalev-Shwartz, Y. Singer, and A. Ng. Online and batch learning of pseudo-metrics. 2004.
21. V. N. Vapnik. Statistical Learning Theory. Wiley-Interscience, 1998.
22. G. Wang, Y. Zhang, and L. Fei-Fei. Using dependent regions for object categorization in a generative framework. In CVPR, 2006.
23. K. Q. Weinberger, J. Blitzer, and L. K. Saul. Distance metric learning for large margin nearest neighbor classification. In NIPS, 2005.
24. E. Xing, A. Ng, and M. Jordan. Distance metric learning with application to clustering with side-information. In NIPS, 2002.
25. H. Zhang, A. Berg,M.Maire, and J. Malik. SVM-KNN: Discriminative Nearset Neighbor Classification for Visual Category Recognition. In CVPR, 2006.