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Gaussian mixture model for video compressive sensing

Publication ,  Journal Article
Yang, J; Yuan, X; Liao, X; Llull, P; Sapiro, G; Brady, DJ; Carin, L
Published in: 2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings
January 1, 2013

A Gaussian Mixture Model (GMM)-based algorithm is proposed for video reconstruction from temporal compressed measurements. The GMM is used to model spatio-temporal video patches, and the reconstruction can be efficiently computed based on analytic expressions. The developed GMM reconstruction method benefits from online adaptive learning and parallel computation. We demonstrate the efficacy of the proposed GMM with videos reconstructed from simulated compressive video measurements and from a real compressive video camera. © 2013 IEEE.

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2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings

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Publication Date

January 1, 2013

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19 / 23
 

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Yang, J., Yuan, X., Liao, X., Llull, P., Sapiro, G., Brady, D. J., & Carin, L. (2013). Gaussian mixture model for video compressive sensing. 2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings, 19–23. https://doi.org/10.1109/ICIP.2013.6738005
Yang, J., X. Yuan, X. Liao, P. Llull, G. Sapiro, D. J. Brady, and L. Carin. “Gaussian mixture model for video compressive sensing.” 2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings, January 1, 2013, 19–23. https://doi.org/10.1109/ICIP.2013.6738005.
Yang J, Yuan X, Liao X, Llull P, Sapiro G, Brady DJ, et al. Gaussian mixture model for video compressive sensing. 2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings. 2013 Jan 1;19–23.
Yang, J., et al. “Gaussian mixture model for video compressive sensing.” 2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings, Jan. 2013, pp. 19–23. Scopus, doi:10.1109/ICIP.2013.6738005.
Yang J, Yuan X, Liao X, Llull P, Sapiro G, Brady DJ, Carin L. Gaussian mixture model for video compressive sensing. 2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings. 2013 Jan 1;19–23.

Published In

2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings

DOI

Publication Date

January 1, 2013

Start / End Page

19 / 23