LEADER 03919nam 22006615 450 001 996547970603316 005 20230315143856.0 010 $a3-030-96530-9 024 7 $a10.1007/978-3-030-96530-3 035 $a(CKB)5580000000524090 035 $a(DE-He213)978-3-030-96530-3 035 $a(EXLCZ)995580000000524090 100 $a20230315d2023 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aComputer Vision$b[electronic resource] $eStatistical Models for Marr's Paradigm /$fby Song-Chun Zhu, Ying Nian Wu 205 $a1st ed. 2023. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2023. 215 $a1 online resource (XIV, 357 p. 192 illus., 109 illus. in color.) 311 $a3-030-96529-5 327 $aPreface -- About the Authors -- 1 Introduction -- 2 Statistics of Natural Images -- 3 Textures -- 4 Textons -- 5 Gestalt Laws and Perceptual Organizations -- 6 Primal Sketch: Integrating Textures and Textons -- 7 2.1D Sketch and Layered Representation -- 8 2.5D Sketch and Depth Maps -- 9 Learning about information Projection -- 10 Informing Scaling and Regimes of Models -- 11 Deep Images and Models -- 12 A Tale of Three Families: Discriminative, Generative and Descriptive Models -- Bibliography. 330 $aAs the first book of a three-part series, this book is offered as a tribute to pioneers in vision, such as Béla Julesz, David Marr, King-Sun Fu, Ulf Grenander, and David Mumford. The authors hope to provide foundation and, perhaps more importantly, further inspiration for continued research in vision. This book covers David Marr's paradigm and various underlying statistical models for vision. The mathematical framework herein integrates three regimes of models (low-, mid-, and high-entropy regimes) and provides foundation for research in visual coding, recognition, and cognition. Concepts are first explained for understanding and then supported by findings in psychology and neuroscience, after which they are established by statistical models and associated learning and inference algorithms. A reader will gain a unified, cross-disciplinary view of research in vision and will accrue knowledge spanning from psychology to neuroscience to statistics. 606 $aImage processing?Digital techniques 606 $aComputer vision 606 $aInformation visualization 606 $aComputer science 606 $aComputer science?Mathematics 606 $aMathematical statistics 606 $aNeural networks (Computer science) 606 $aComputer Imaging, Vision, Pattern Recognition and Graphics 606 $aData and Information Visualization 606 $aTheory of Computation 606 $aProbability and Statistics in Computer Science 606 $aComputer Science 606 $aMathematical Models of Cognitive Processes and Neural Networks 615 0$aImage processing?Digital techniques. 615 0$aComputer vision. 615 0$aInformation visualization. 615 0$aComputer science. 615 0$aComputer science?Mathematics. 615 0$aMathematical statistics. 615 0$aNeural networks (Computer science). 615 14$aComputer Imaging, Vision, Pattern Recognition and Graphics. 615 24$aData and Information Visualization. 615 24$aTheory of Computation. 615 24$aProbability and Statistics in Computer Science. 615 24$aComputer Science. 615 24$aMathematical Models of Cognitive Processes and Neural Networks. 676 $a006 700 $aZhu$b Song-Chun$4aut$4http://id.loc.gov/vocabulary/relators/aut$01254935 702 $aWu$b Ying Nian$4aut$4http://id.loc.gov/vocabulary/relators/aut 906 $aBOOK 912 $a996547970603316 996 $aComputer Vision$93331956 997 $aUNISA LEADER 00910nas0 22002773i 450 001 TO00193420 005 20231121125835.0 017 70$aP 00060151$2P 100 $a20150429b19331946||||0itac50 ba 101 | $afre 102 $afr 110 $aa|u|||||||| 181 1$6z01$ai $bxxxe 182 1$6z01$an 200 1 $aRevue d'histoire de la philosophie et d'histoire generale de la civilisation 207 0$a1933-1946 210 $aParis$cLibrairie universitaire J. Gamber$d1933-1946 215 $av.$d26 cm 300 $aTrimestrale. 430 0$1001TO00306637$12001 $aRevue d'histoire de la philosophie 440 1 $1001MIL0055411$12001 $aRSH$eRevue des sciences humaines$fUniversité Charles-de-Gaulle 801 3$aIT$bIT-01$c20150429 912 $aTO00193420 977 $a 52 996 $aRevue d'histoire de la philosophie et d'histoire generale de la civilisation$93637730 997 $aUNICAS