Adaptive-Rate Sparse Signal Reconstruction With Application in
Compressive Background Subtraction

Adaptive-Rate Sparse Signal Reconstruction With Application in Compressive Background Subtraction

11 March 2015

João F. C. Mota

Nikos Deligiannis

Aswin C. Sankaranarayanan

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Papers citing "Adaptive-Rate Sparse Signal Reconstruction With Application in Compressive Background Subtraction"

5 / 5 papers shown

Title
On the Role and the Importance of Features for Background Modeling and Foreground Detection T. Bouwmans Caroline Silva C. Marghes M. S. Zitouni H. Bhaskar C. Frélicot 37 108 0 28 Nov 2016
Measurement Bounds for Sparse Signal Reconstruction with Multiple Side Information Huynh Van Luong Jürgen Seiler Andre Kaup Søren Forchhammer Nikos Deligiannis 41 4 0 10 May 2016
Decomposition into Low-rank plus Additive Matrices for Background/Foreground Separation: A Review for a Comparative Evaluation with a Large-Scale Dataset T. Bouwmans A. Sobral S. Javed Soon Ki Jung E. Zahzah 99 332 0 04 Nov 2015
Total Variation Regularized Tensor RPCA for Background Subtraction from Compressive Measurements Wenfei Cao Yao Wang Jian Sun Deyu Meng Can Yang A. Cichocki Zongben Xu 160 161 0 06 Mar 2015
Classification and Reconstruction of High-Dimensional Signals from Low-Dimensional Features in the Presence of Side Information F. Renna Liming Wang Xin Yuan Jianbo Yang Galen Reeves Robert Calderbank Lawrence Carin M. Rodrigues 52 45 0 01 Dec 2014