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Adaptive-Rate Reconstruction of Time-Varying Signals With Application in Compressive Foreground Extraction

Mota, JFC; Deligiannis, N; Sankaranarayanan, AC; Cevher, V; Rodrigues, MRD; (2016) Adaptive-Rate Reconstruction of Time-Varying Signals With Application in Compressive Foreground Extraction. IEEE TRANSACTIONS ON SIGNAL PROCESSING , 64 (14) pp. 3651-3666. 10.1109/TSP.2016.2544744. Green open access

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Abstract

We propose and analyze an online algorithm for reconstructing a sequence of signals from a limited number of linear measurements. The signals are assumed sparse, with unknown support, and evolve over time according to a generic nonlinear dynamical model. Our algorithm, based on recent theoretical results for l1 - l1 minimization, is recursive and computes the number of measurements to be taken at each time on-the-fly. As an example, we apply the algorithm to online compressive video foreground extraction, a problem stated as follows: given a set of measurements of a sequence of images with a static background, simultaneously reconstruct each image while separating its foreground from the background. The performance of our method is illustrated on sequences of real images. We observe that it allows a dramatic reduction in the number of measurements or reconstruction error with respect to state-of-the-art compressive background subtraction schemes.

Type: Article
Title: Adaptive-Rate Reconstruction of Time-Varying Signals With Application in Compressive Foreground Extraction
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/TSP.2016.2544744
Publisher version: http://dx.doi.org/10.1109/TSP.2016.2544744
Language: English
Additional information: This work is licensed under a Creative Commons Attribution 3.0 License. For more information, see http://creativecommons.org/licenses/by/3.0/
Keywords: Science & Technology, Technology, Engineering, Electrical & Electronic, Engineering, Background subtraction, compressive video, l(1) minimization, motion estimation, sparsity, state estimation, LEAST-SQUARES, BACKGROUND SUBTRACTION, MATRIX DECOMPOSITION, BASIS PURSUIT, DYNAMIC MRI, ROBUST PCA, SPARSE, UNCERTAINTY, RECOVERY, SYSTEMS
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/1508361
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