LEADER 00837nam0-2200301---450- 001 990009413070403321 005 20110831115225.0 010 $a978-88-6381-018-9 035 $a000941307 035 $aFED01000941307 035 $a(Aleph)000941307FED01 035 $a000941307 100 $a20110831d2009----km-y0itay50------ba 101 0 $aita 102 $aIT 105 $a--------001yy 200 1 $a<>Costituzione italiana$eguida alla lettura$fRita Diddi Nardi e Rossana Coen 210 $aNapoli$cScripta Web$d2009 215 $a265 p.$d20 cm 700 1$aDiddi Nardi,$bRita$0327646 701 1$aCoen,$bRossana$0317638 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990009413070403321 952 $aVII 138$b7477$fDDCIC 959 $aDDCIC 996 $aCostituzione italiana$9759269 997 $aUNINA LEADER 03615nam 2200601Ia 450 001 9910437926303321 005 20200520144314.0 010 $a9783642286612 010 $a3642286615 024 7 $a10.1007/978-3-642-28661-2 035 $a(CKB)3390000000030165 035 $a(SSID)ssj0000746033 035 $a(PQKBManifestationID)11412859 035 $a(PQKBTitleCode)TC0000746033 035 $a(PQKBWorkID)10863287 035 $a(PQKB)10425304 035 $a(DE-He213)978-3-642-28661-2 035 $a(MiAaPQ)EBC3070812 035 $a(PPN)168312468 035 $a(EXLCZ)993390000000030165 100 $a20120807d2013 uy 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 00$aMachine learning for computer vision /$fRoberto Cipolla, Sebastiano Battiato, and Giovanni Maria Farinella (eds.) 205 $a1st ed. 2013. 210 $aBerlin ;$aNew York $cSpringer$dc2013 215 $a1 online resource (XXII, 250 p.) 225 1 $aStudies in computational intelligence,$x1860-949X ;$v411 300 $aBibliographic Level Mode of Issuance: Monograph 311 08$a9783642286605 311 08$a3642286607 320 $aIncludes bibliographical references. 327 $aThrowing Down the Visual Intelligence Gauntlet -- Actionable Information in Vision -- Learning Binary Hash Codes for Large-Scale Image Search -- Bayesian Painting by Numbers: Flexible Priors for Colour-Invariant Object Recognition -- Real-Time Human Pose Recognition in Parts from Single Depth Images -- Scale-Invariant Vote-based 3D Recognition and Registration from Point Clouds -- Multiple Classifier Boosting and Tree-Structured Classifiers -- Simultaneous detection and tracking with multiple cameras -- Applications of Computer Vision to Vehicles: an extreme test. 330 $aComputer vision is the science and technology of making machines that see. It is concerned with the theory, design and implementation of algorithms that can automatically process visual data to recognize objects, track and recover their shape and spatial layout. The International Computer Vision Summer School - ICVSS was established in 2007 to provide both an objective and clear overview and an in-depth analysis of the state-of-the-art research in Computer Vision. The courses are delivered by world renowned experts in the field, from both academia and industry, and cover both theoretical and practical aspects of real Computer Vision problems. The school is organized every year by University of Cambridge (Computer Vision and Robotics Group) and University of Catania (Image Processing Lab). Different topics are covered each year. A summary of the past Computer Vision Summer Schools can be found at: http://www.dmi.unict.it/icvss This edited volume contains a selection of articles covering some of the talks and tutorials held during the last editions of the school. The chapters provide an in-depth overview of challenging areas with key references to the existing literature. 410 0$aStudies in computational intelligence ;$vv. 411. 606 $aComputer vision$vCongresses 606 $aMachine learning$vCongresses 615 0$aComputer vision 615 0$aMachine learning 676 $a006.3/7 701 $aCipolla$b Roberto$030498 701 $aBattiato$b Sebastiano$0760170 701 $aFarinella$b Giovanni Maria$01262568 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910437926303321 996 $aMachine learning for computer vision$94204129 997 $aUNINA