{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/adaptive-rate-sparse-signal-reconstruction","title":"Adaptive-Rate Sparse Signal Reconstruction With Application in Compressive Background Subtraction","arxiv_id":"1503.03231","date":"2015-03-11","proceeding":null,"authors":["Joao F. C. Mota","Nikos Deligiannis","Aswin C. Sankaranarayanan","Volkan Cevher","Miguel R. D. Rodrigues"],"abstract":"We propose and analyze an online algorithm for reconstructing a sequence of\nsignals from a limited number of linear measurements. The signals are assumed\nsparse, with unknown support, and evolve over time according to a generic\nnonlinear dynamical model. Our algorithm, based on recent theoretical results\nfor $\\ell_1$-$\\ell_1$ minimization, is recursive and computes the number of\nmeasurements to be taken at each time on-the-fly. As an example, we apply the\nalgorithm to compressive video background subtraction, a problem that can be\nstated as follows: given a set of measurements of a sequence of images with a\nstatic background, simultaneously reconstruct each image while separating its\nforeground from the background. The performance of our method is illustrated on\nsequences of real images: we observe that it allows a dramatic reduction in the\nnumber of measurements with respect to state-of-the-art compressive background\nsubtraction schemes.","url_abs":"http://arxiv.org/abs/1503.03231v1","url_pdf":"http://arxiv.org/pdf/1503.03231v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"adaptive-rate-sparse-signal-reconstruction","repo_url":"https://github.com/joaofcmota/AdaptiveRateCompressiveForegroundExtraction","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"adaptive-rate-sparse-signal-reconstruction","repo_url":"https://github.com/FaceOnLive/Realtime-Background-Changer-SDK-Android","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"video-background-subtraction","task_name":"Video Background Subtraction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}