A principal component regression strategy for estimating motion - researchr publication references

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Vania Vieira Estrela, Marcos Henrique da Silva Bassani, Joaquim Teixeira de Assis, Vânia Vieira Estrela. A principal component regression strategy for estimating motion. In The Seventh IASTED International Conference on Visualization, Imaging and Image Processing. VIIP '07, pages 224-228, ACTA Press, Anaheim, CA, USA, 2007.

A pel-recursive Wiener based displacement estimation algorithmJ. Biemond, L. Looijenga, D. E. Boekee, R. H. J. M. Plompen. Signal Processing, 13:399-412, 1987.

A Spatially-Constrained Mixture Model for Image SegmentationBlekas, K., Likas, A., Galatsanos, N. P., Lagaris. I.E., Konstantinos Blekas, Aristidis Likas, A., Nikolas P. Galatsanos, I. E. Lagaris. IEEE Tansactions on Neural Networks, 16:494-498, 2005.

Regression analysis by exampleS. Chattefuee, A. S. Hadi. John Wiley&Sons, Inc., 2006.

Spatially-Adaptive Regularized Pel-Recursive Motion Estimation based on Cross-ValidationVania Vieira Estrela, Nikolas P. Galatsanos, Nikolas P. Galatsanos, Vania Vieira Estrela, Vania Vieira Estrela, Vania Vieira Estrela. icip 1998: 200-203 [doi]

Expectation-Maximization Technique and Spatial Adaptation Applied to Pel-Recursive Motion EstimationVania Vieira Estrela, Marcos Henrique da Silva Bassani, Vania Vieira Estrela, Marcos Henrique da Silva Bassani, Vania Vieira Estrela, Marcos Henrique da Silva Bassani. 2004:

Wide-field, motion-sensitive neurons and matched filters for optic flow fieldsMatthias O. Franz, Holger G. Krapp. bc, 83(3):185-197, 2000. [doi]

Linear combinations of optic flow vectors for estimating self-motion - a real-world test of a neural modelM. O. Franz, J. S. Chahl. In Advances in Neural Information Processing Systems 15. 2003: 1343-1350

Introduction to statistical pattern recognitionKeinosuke Fukunaga. Academic Press Professional, Inc., 1990.

Methods for choosing the regularization parameter and estimating the noise variance in image restoration and their relationNikolas P. Galatsanos, Aggelos K. Katsaggelos. TIP, 1(3):322-336, 1992. [doi]

Neural Networks: A Comprehensive FoundationSimon Haykin. Prentice Hall PTR, 1998.

A user's guide to principal componentsJ. E. Jackson. John Wiley & Sons, 1991.

Principal component analysisI. Jolliffe. Springer-Verlag, 1986.

Iterative Kernel Principal Component Analysis for Image ModelingKwang In Kim, Matthias O. Franz, Bernhard Schölkopf. pami, 27(9):1351-1366, 2005. [doi]

Digital Video ProcessingM. Tekalp. Prentice Hall, 1995.

Probabilistic principal component analysisM. E. Tipping, C. M. Bishop. J. R. Statist. Soc. B, 61:611-622, 1999.

Food Research and Data AnalysisS. Wold, C. Albano, W. J. Dunn, K. Esbensen, S. Hellberg. pages 147-188, 1983.

EM-Based Mixture Models Applied to Video Event DetectionAlessandra Martins Coelho, Vania Vieira Estrela, Vania Vieira Estrela, Vania Vieira Estrela, Vania Vieira Estrela, Vania Vieira Estrela, Vania Vieira Estrela, Alessandra Martins Coelho. Printed and online, 2012.

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