MARC Record from marc_columbia

LEADER: 05390cam a2200661 i 4500
001 15100657
005 20221119231848.0
006 m o d
007 cr |||||||||||
008 140719t20152015flua ob 001 0 eng d
035 $a(OCoLC)ocn884012672
035 $a(NNC)15100657
040 $aEBLCP$beng$erda$epn$cEBLCP$dCUS$dN$T$dWAU$dE7B$dOCLCO$dSTF$dYDXCP$dCRCPR$dOCLCQ$dCOO$dOCLCQ$dIDEBK$dUMI$dDEBBG$dDEBSZ$dOCLCF$dCSAIL$dOCLCQ$dCDX$dMOR$dPIFBY$dOTZ$dMERUC$dOCLCQ$dUAB$dOCLCQ$dUUM$dOCLCQ$dCEF$dOCLCQ$dU3W$dOCLCQ$dS9I$dYDX$dTYFRS$dLEAUB$dAU@$dOCLCQ$dUHL$dOCLCQ$dOCLCO$dOCLCQ
019 $a889309947$a900646129$a903000132$a988465824
020 $a9781482205381$q(electronic bk.)
020 $a1482205386$q(electronic bk.)
020 $a1482205378
020 $a9781482205374
020 $a9781322636795
020 $a1322636796
020 $z9781482205374
024 7 $a10.1201/b17223$2doi
035 $a(OCoLC)884012672$z(OCoLC)889309947$z(OCoLC)900646129$z(OCoLC)903000132$z(OCoLC)988465824
037 $aCL0500000534$bSafari Books Online
050 4 $aTK6680.3
072 7 $aTEC$x009070$2bisacsh
082 04 $a621.389/28$223
049 $aZCUA
245 00 $aBackground modeling and foreground detection for video surveillance /$cedited by Thierry Bouwmans, Fatih Porikli, Benjamin Höferlin, Antoine Vacavant.
264 1 $aBoca Raton, FL :$bCRC Press/Taylor & Francis Group,$c[2015]
264 4 $c©20
264 4 $c©2015
300 $a1 online resource (xvix, 633 pages) :$billustrations
336 $atext$btxt$2rdacontent
337 $acomputer$bc$2rdamedia
338 $aonline resource$bcr$2rdacarrier
347 $adata file
504 $aIncludes bibliographical references and index.
588 0 $aPrint version record.
505 0 $aFront Cover; Dedication; Contents; Preface; About the Editors; List of Contributors; I: Introduction and Background; 1. Traditional Approaches in Background Modeling for Static Cameras; 2. Recent Approaches in Background Modeling for Static Cameras; 3. Background Model Initialization for Static Cameras; 4. Background Subtraction for Moving Cameras; II: Traditional and Recent Models; 5. Statistical Models for Background Subtraction; 6. Non-parametric Background Segmentation with Feedback and Dynamic Controllers; 7. ViBe: A Disruptive Method for Background Subtraction.
505 8 $a8. Online Learning by Stochastic Approximation for Background Modeling9. Sparsity Driven Background Modeling and Foreground Detection; 10. Robust Detection of Moving Objects through Rough Set Theory Framework; III: Applications in Video Surveillance; 11. Background Learning with Support Vectors: Efficient Foreground Detection and Tracking for Automated Visual Surveillance; 12. Incremental Learning of an Infinite Beta-Liouville Mixture Model for Video Background Subtraction; 13. Spatio-temporal Background Models for Object Detection.
505 8 $a14. Background Modeling and Foreground Detection for Maritime Video Surveillance15. Hierarchical Scene Model for Spatial-color Mixture of Gaussians; 16. Online Robust Background Modeling via Alternating Grassmannian Optimization; IV: Sensors, Hardware and Implementations; 17. Ubiquitous Imaging (Light, Thermal, Range, Radar) Sensors for People Detection: An Overview; 18. RGB-D Cameras for Background-Foreground Segmentation; 19. Non-Parametric GPU Accelerated Background Modeling of Complex Scenes.
505 8 $a20. GPU Implementation for Background-Foreground-Separation via Robust PCA and Robust Subspace Tracking21. Background Subtraction on Embedded Hardware; 22. Resource-efficient Salient Foreground Detection for Embedded Smart Cameras; V: Benchmarking and Evaluation; 23. BGS Library: A Library Framework for Algorithms Evaluation in Foreground/Background Segmentation; 24. Overview and Benchmarking of Motion Detection Methods; 25. Evaluation of Background Models with Synthetic and Real Data; Color Insert.
520 $aBackground modeling and foreground detection are important steps in video processing used to detect robustly moving objects in challenging environments. This requires effective methods for dealing with dynamic backgrounds and illumination changes as well as algorithms that must meet real-time and low memory requirements. Incorporating both established and new ideas, Background Modeling and Foreground Detection for Video Surveillance provides a complete overview of the concepts, algorithms, and applications related to background modeling and foreground detection.
650 0 $aVideo surveillance.
650 0 $aOptical pattern recognition.
650 6 $aVidéosurveillance.
650 6 $aReconnaissance optique des formes (Informatique)
650 7 $aTECHNOLOGY & ENGINEERING$xMechanical.$2bisacsh
650 7 $aOptical pattern recognition.$2fast$0(OCoLC)fst01046784
650 7 $aVideo surveillance.$2fast$0(OCoLC)fst01748635
700 1 $aBouwmans, Thierry,$eeditor.
700 1 $aPorikli, Fatih,$eeditor.
700 1 $aHöferlin, Benjamin,$eeditor.
700 1 $aVacavant, Antoine,$eeditor.
776 08 $iPrint version:$tBackground modeling and foreground detection for video surveillance.$dBoca Raton, Florida : CRC Press, [2015]$z9781482205374$w(OCoLC)859584240
856 40 $uhttp://www.columbia.edu/cgi-bin/cul/resolve?clio15100657$zTaylor & Francis eBooks
852 8 $blweb$hEBOOKS