Transformation invariant component analysis for binary images

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

Volumn 1, Issue , 2006, Pages 254-259

  Zivkovic, Zoran ^a   Verbeek, Jakob ^b  

^a UNIVERSITY OF AMSTERDAM   (Netherlands)

^b GRAVIR INRIA   (France)

Author keywords

[No Author keywords available]

Indexed keywords

BERNOULLI DISTRIBUTIONS; BINARY DATA; BINARY IMAGES; DATA ALIGNMENT;

CHARACTER RECOGNITION; IMAGE SEGMENTATION; INVARIANCE; MATHEMATICAL MODELS; MATHEMATICAL TRANSFORMATIONS; PRINCIPAL COMPONENT ANALYSIS;

IMAGE ANALYSIS;

EID: 33845572353     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2006.316     Document Type: Conference Paper

References (14)

1. M. Black and A. Jepson. Eigen Tracking: Robust matching and tracking of articulated objects using a view-based representation. International Journal of Computer Vision, 26(1):63-84, 1998.
2. A. Dempster, N. Laird, and D. Rubin. Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society, Series B (Methodological), 1(39): 1-38, 1977.
3. B. Frey and N. Jojic. Transformation-invariant clustering using the EM algorithm. IEEE Trans. on Pattern Analysis and Machine Intelligence, 25:1-17, 2003.
4. G. Hinton, P. Dayan, and M. Revow. Modeling the manifolds of images of handwritten digits. IEEE Transactions on Neural Networks, 8:65-74, 1997.
5. N. Jojic, N. Petrovic, B. Frey, and T. Huang. Transformed hidden markov models: Estimating mixture models and inferring spatial transformations in video sequences. In Proc. IEEE Conf. on Computer Vision and Pattern Recognition, 2000.
6. A. Kannan, N. Jojic, and B. Frey. Fast transformation-invariant component analysis (or factor analysis). In Advances in Neural Information Processing Systems (NIPS), 2003.
7. Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner. Gradient-based learning applied to document recognition. Proceedings of the IEEE, 86(11):2278-2324, 1998.
8. A. Schein, L. Saul, and L. Ungar. A generalized linear model for principal component analysis of binary data. In Proc. Int. Workshop on Artificial Intelligence and Statistics, pages 14-21, 2003.
9. M. Tipping. Probabilistic visualisation of high-dimensional binary data. In Advances in Neural Information Processing Systems (NIPS), 1999.
10. M. Tipping and C. Bishop. Mixture of probabilistic principal component analyzers. Neural Computation, 11(2):443-483, 1999.
11. M. Turk and A. Pentland. Eigenfaces for recognition. Journal of Cognitive Neuroscience, 3:71-86, 1991.
12. J. Wang and E. Adelson. Layered representation for motion analysis. In Proc. IEEE Conf. on Computer Vision and Pattern Recognition, pages 361-366, 1993.
13. G. Wolberg and S. Zokai. Robust image registration using log-polar transform. In Proc. IEEE Int. Conf. image processing, vol. 1, pages 493-496, 2000.
14. Z.Zivkovic and F. der Heijden. Efficient adaptive density estimation per image pixel for the task of background subtraction. Pattern Recognition Letters, 27(7):773-780, 2006.