Towards a theory of compositional learning and encoding of objects

Proceedings of the IEEE International Conference on Computer Vision

Volumn , Issue , 2011, Pages 1448-1455

  Yuille, A L ^a,b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b Korea University   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

COMPOSITIONAL MODELS; COMPOSITIONALITY; GRAPHICAL MODEL; PROBABILITY MODELS; THEORETICAL BASIS;

LEARNING ALGORITHMS;

IMAGE PROCESSING;

EID: 84856675237     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCVW.2011.6130421     Document Type: Conference Paper

References (14)

1. A. P. Benavent, F. E. Ruiz, and J. M. Śaez. Learning gaussian mixture models with entropy-based criteria. IEEE Transactions on Neural Networks, 20(11):1756-1771, 2009.
2. S. Fidler, M. Boben, and A. Leonardis. Similarity-based cross-layered hierarchical representation for object categorization. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2008.
3. Y. Jin and S. Geman. Context and hierarchy in a probabilistic image model. In CVPR (2), pages 2145-2152, 2006.
4. Y. Ma, S. Member, H. Derksen, W. Hong, J. Wright, and S. Member. Segmentation of multivariate mixed data via lossy coding and compression. IEEE Transactions on Pattern Analysis and Machine Intelligence, 3, 2007.
5. B. Ommer and J. M. Buhmann. Learning compositional categorization models. In Proceedings of the European Conference on Computer Vision (ECCV), 2006.
6. S. D. Pietra, V. J. D. Pietra, and J. D. Lafferty. Inducing features of random fields. IEEE Trans. Pattern Anal. Mach. Intell., 19(4):380-393, 1997.
7. J. Rissanen. Modeling by shortest data description. Automatica, 14(5):465-471, 1978.
8. C. Shannon. Prediction and entropy of printed english. The Bell System Technical Journal, 30:50-64, 1951.
9. Y. Wu, Z. Si, H. Gong, and S. Zhu. Learning active basis model for object detection and recognition. Intl. Journal of Computer Vision (IJCV), 2009.
10. A. L. Yuille, J. Coughlan, Y. Wu, and S. Zhu. Order parameters for detecting target curves in images: When does highlevel knowledge help? International Journal of Computer Vision, 41(1/2):9-33, 2001.
11. L. Zhu, Y. Chen, A. Torralba, W. Freeman, and A. Yuille. Part and appearance sharing: Recursive compositional models for multi-view multi-object detection. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2010.
12. L. Zhu, Y. Chen, and A. L. Yuille. Unsupervised learning of probabilistic grammar-markov models for object categories. In Transactions on Pattern Analysis and Machine Intelligence, pages 114-128, 2009.
13. L. Zhu, C. Lin, H. Huang, Y. Chen, and A. Yuille. Unsupervised structure learning: Hierarchical recursive composition, suspicious coincidence and competitive exclusion. In Proceedings of the European Conference on Computer Vision (ECCV), 2008.
14. S. C. Zhu, Y. N. Wu, and D. Mumford. Minimax entropy principle and its application to texture modeling. Neural Computation, 9(8):1627-1660, 1997.