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A Self-adaptive CodeBook (SACB) model for real-time background subtraction.

, , and . Image Vision Comput., (2015)

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Video background modeling: recent approaches, issues and our proposed techniques., , and . Mach. Vis. Appl., 25 (5): 1105-1119 (2014)Illumination Invariant Background Model Using Mixture of Gaussians and SURF Features., , and . ACCV Workshops (1), volume 7728 of Lecture Notes in Computer Science, page 308-314. Springer, (2012)Growing Neural Gas Video Background Model (GNG-BM)., , and . Australasian Conference on Artificial Intelligence, volume 8272 of Lecture Notes in Computer Science, page 135-147. Springer, (2013)Enhancing the mixture of Gaussians background model with local matching and local adaptive learning., , and . IVCNZ, page 103-108. ACM, (2012)Improving Mixture of Gaussians background model through adaptive learning and Spatio-Temporal voting., , and . ICIP, page 3436-3440. IEEE, (2013)Enhanced Codebook Model for Real-Time Background Subtraction., , and . ICONIP (3), volume 7064 of Lecture Notes in Computer Science, page 449-458. Springer, (2011)A Self-adaptive CodeBook (SACB) model for real-time background subtraction., , and . Image Vision Comput., (2015)Intelligent On-Demand Connectivity Restoration for Wireless Sensor Networks., , , , , and . Wireless Communications and Mobile Computing, (2018)Optimal job packing, a backfill scheduling optimization for a cluster of workstations., , and . The Journal of Supercomputing, 54 (3): 381-399 (2010)Empirical performance evaluation of schedulers for cluster of workstations., , and . Cluster Computing, 14 (2): 101-113 (2011)