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.
Duke Scholars
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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