Background subtraction are generally made in the context of real-time application on common PC or on smart embedded cameras. So, the computation time and memory requirement need to be reduced as possible. Real-time implementations focus mainly on the following issues:
GPU Implementations (43 papers)
Embedded Implementations (38 papers)
Architecture Implementations (54 papers)
Parallel Implementations (10 papers)
Quantum Computing (1 paper)
Near-sensor Implementations (1 paper)
Author: Thierry BOUWMANS, Associate Professor, Lab. MIA, Univ. Rochelle, France.
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As this website gives many information that come from my research, please cite my following survey papers:
T. Bouwmans, “Traditional and Recent Approaches in Background Modeling for Foreground Detection: An Overview”, Computer Science Review, 2014. [pdf]
T. Bouwmans, E. Zahzah, “Robust PCA via Principal Component Pursuit: A Review for a Comparative Evaluation in Video Surveillance”, Special Issue on Background Models Challenge, Computer Vision and Image Understanding, CVIU 2014, Volume 122, pages 22–34, May 2014. [pdf]
T. Bouwmans, "Recent Advanced Statistical Background Modeling for Foreground Detection: A Systematic Survey", Recent Patents on Computer Science, Volume 4, No. 3, pages147-176, September 2011. [pdf]
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