Unsupervised learning of categories from sets of partially matching image features

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn 1, Issue , 2006, Pages 19-25

  Grauman, Kristen ^a   Darrell, Trevor ^a  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

PARTIALLY MATCHING IMAGE FEATURES; SPECTRAL CLUSTERING TECHNIQUE; UNLABELED IMAGES; UNSUPERVISED LEARNING;

ALGORITHMS; CLASSIFICATION (OF INFORMATION); COMPUTATION THEORY; IMAGE ANALYSIS; LEARNING SYSTEMS; SET THEORY;

PATTERN MATCHING;

EID: 33845575890     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2006.322     Document Type: Conference Paper

References (14)

1. S. Belongie, J. Malik, and J. Puzicha. Shape Matching and Object Recognition Using Shape Contexts. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(24):509-522, April 2002.
2. A. Berg, T. Berg, and J. Malik. Shape Matching and Object Recognition using Low Distortion Correspondences. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, San Diego, CA, June 2005.
3. R. Fergus, L. Fei-Fei, P. Perona, and A. Zisserman. Learning Object Categories from Google's Im age Search. In Proceedings of the IEEE International Conference on Computer Vision, Beijing, China, October 2005.
4. K. Grauman and T. Darrell. The Pyramid Match Kernel: Discriminative Classification with Sets of Image Features. In Proceedings of the IEEE International Conference on Computer Vision, Beijing, China, October 2005.
5. K. Grauman and T. Darrell. Pyramid Match Kernels: Discriminative Classification with Sets of Image Features. Technical Report MIT-CSAIL-TR-2006-020, MIT, March 2006.
6. S. Kamvar, D. Klein, and C. Manning. Spectral Learning. In Proceedings of the International Conference on Artificial Intelligence, Acapulco, Mexico, August 2003.
7. D. Lowe. Distinctive Image Features from Scale-Invariant Keypoints. International Journal of Computer Vision, 60(2):91-110, January 2004.
8. K. Mikolajczyk and C. Schmid. Indexing Based on Scale Invariant Interest Points. In Proceedings of the IEEE International Conference on Computer Vision, Vancouver, Canada, July 2001.
9. K. Mikolajczyk and C. Schmid. Scale and Affine Invariant Interest Point Detectors. International Journal of Computer Vision, 1(60):63-86, October 2004.
10. P. Quelhas, F. Monay, J.-M. Odobez, D. Gatica-Perez, T. Tuytelaars, and L. VanGool. Modeling Scenes with Local Descriptors and Latent Aspects. In Proceedings of the IEEE International Conference on Computer Vision, Beijing, China, October 2005.
11. J. Shi and J. Malik. Normalized Cuts and Image Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(8):888-905, August 2000.
12. J. Sivic, B. Russell, A. Efros, A. Zisserman, and W. Freeman. Discovering Object Categories in Image Collections. In Proceedings of the IEEE International Conference on Computer Vision, Beijing, China, October 2005.
13. C. Williams and M. Seeger. Using the Nystrom Method to Speed Up Kernel Machines. In Advances in Neural Information Processing, 2001.
14. L. Zelnik-Manor and P. Perona. Self-Tuning Spectral Clustering. In Advances in Neural Information Processing, Vancouver, Canada, December 2004.