LEADER 06325nam 22008415 450 001 996466356103316 005 20200704100126.0 010 $a3-540-30212-3 024 7 $a10.1007/b104157 035 $a(CKB)1000000000212656 035 $a(SSID)ssj0000251105 035 $a(PQKBManifestationID)11206753 035 $a(PQKBTitleCode)TC0000251105 035 $a(PQKBWorkID)10248323 035 $a(PQKB)11414926 035 $a(DE-He213)978-3-540-30212-4 035 $a(MiAaPQ)EBC3087406 035 $a(PPN)155191357 035 $a(EXLCZ)991000000000212656 100 $a20121227d2004 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aStatistical Methods in Video Processing$b[electronic resource] $eECCV 2004 Workshop SMVP 2004, Prague, Czech Republic, May 16, 2004, Revised Selected Papers /$fedited by Dorin Comaniciu, Kenichi Kanatani, Rudolf Mester, David Suter 205 $a1st ed. 2004. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2004. 215 $a1 online resource (VIII, 200 p.) 225 1 $aLecture Notes in Computer Science,$x0302-9743 ;$v3247 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-540-23989-8 320 $aIncludes bibliographical references and index. 327 $a3D Geometry -- Towards Complete Free-Form Reconstruction of Complex 3D Scenes from an Unordered Set of Uncalibrated Images -- Geometric Structure of Degeneracy for Multi-body Motion Segmentation -- Virtual Visual Hulls: Example-Based 3D Shape Inference from Silhouettes -- Unbiased Errors-In-Variables Estimation Using Generalized Eigensystem Analysis -- Tracking -- Probabilistic Tracking of the Soccer Ball -- Multi-Model Component-Based Tracking Using Robust Information Fusion -- A Probabilistic Approach to Large Displacement Optical Flow and Occlusion Detection -- Mean-Shift Blob Tracking with Kernel-Color Distribution Estimate and Adaptive Model Update Criterion -- Combining Simple Models to Approximate Complex Dynamics -- Background Modeling -- Online Adaptive Gaussian Mixture Learning for Video Applications -- Novelty Detection in Image Sequences with Dynamic Background -- A Framework for Foreground Detection in Complex Environments -- A Background Maintenance Model in the Spatial-Range Domain -- Image/Video Analysis -- A New Robust Technique for Stabilizing Brightness Fluctuations in Image Sequences -- Factorization of Natural 4 × 4 Patch Distributions -- Parametric and Non-parametric Methods for Linear Extraction -- Crowd Segmentation Through Emergent Labeling. 330 $aThe 2nd International Workshop on Statistical Methods in Video Processing, SMVP 2004, was held in Prague, Czech Republic, as an associated workshop of ECCV 2004, the 8th European Conference on Computer Vision. A total of 30 papers were submitted to the workshop. Of these, 17 papers were accepted for presentation and included in these proceedings, following a double-blind review process. The workshop had 42 registered participants. The focus of the meeting was on recent progress in the application of - vanced statistical methods to solve computer vision tasks. The one-day scienti?c program covered areas of high interest in vision research, such as dense rec- struction of 3D scenes, multibody motion segmentation, 3D shape inference, errors-in-variables estimation, probabilistic tracking, information fusion, optical ?owcomputation,learningfornonstationaryvideodata,noveltydetectionin- namic backgrounds, background modeling, grouping using feature uncertainty, and crowd segmentation from video. We wish to thank the authors of all submitted papers for their interest in the workshop.Wealsowishtothankthemembersofourprogramcommitteeandthe external reviewers for their commitment of time and e?ort in providing valuable recommendations for each submission. We are thankful to Vaclav Hlavac, the General Chair of ECCV 2004, and to Radim Sara, for the local organization of the workshop and registration management. We hope you will ?nd these proceedings both inspiring and of high scienti?c quality. 410 0$aLecture Notes in Computer Science,$x0302-9743 ;$v3247 606 $aOptical data processing 606 $aComputer graphics 606 $aPattern recognition 606 $aMathematical statistics 606 $aArtificial intelligence 606 $aAlgorithms 606 $aImage Processing and Computer Vision$3https://scigraph.springernature.com/ontologies/product-market-codes/I22021 606 $aComputer Graphics$3https://scigraph.springernature.com/ontologies/product-market-codes/I22013 606 $aPattern Recognition$3https://scigraph.springernature.com/ontologies/product-market-codes/I2203X 606 $aProbability and Statistics in Computer Science$3https://scigraph.springernature.com/ontologies/product-market-codes/I17036 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aAlgorithm Analysis and Problem Complexity$3https://scigraph.springernature.com/ontologies/product-market-codes/I16021 615 0$aOptical data processing. 615 0$aComputer graphics. 615 0$aPattern recognition. 615 0$aMathematical statistics. 615 0$aArtificial intelligence. 615 0$aAlgorithms. 615 14$aImage Processing and Computer Vision. 615 24$aComputer Graphics. 615 24$aPattern Recognition. 615 24$aProbability and Statistics in Computer Science. 615 24$aArtificial Intelligence. 615 24$aAlgorithm Analysis and Problem Complexity. 676 $a006.3/7 702 $aComaniciu$b Dorin$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aKanatani$b Kenichi$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aMester$b Rudolf$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aSuter$b David$4edt$4http://id.loc.gov/vocabulary/relators/edt 712 12$aStatistical Methods in Video Processing Workshop 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996466356103316 996 $aStatistical Methods in Video Processing$92092077 997 $aUNISA