LEADER 02876oam 2200469 450 001 9910299492303321 005 20190911112725.0 010 $a3-319-00711-4 024 7 $a10.1007/978-3-319-00711-3 035 $a(OCoLC)877107232 035 $a(MiFhGG)GVRL6XSV 035 $a(EXLCZ)992670000000423538 100 $a20130502d2014 uy 0 101 0 $aeng 135 $aurun|---uuuua 181 $ctxt 182 $cc 183 $acr 200 10$aComputer vision analysis of image motion by variational methods /$fAmar Mitiche, J.K. Aggarwal 205 $a1st ed. 2014. 210 1$aCham, Switzerland :$cSpringer,$d2014. 215 $a1 online resource (vii, 207 pages) $cillustrations (some color) 225 1 $aSpringer Topics in Signal Processing,$x1866-2609 ;$v10 300 $a"ISSN: 1866-2609." 311 $a3-319-00710-6 320 $aIncludes bibliographical references and index. 327 $aImage Motion Processing in Visual Function -- Background Preliminaries -- Optical Flow Estimation -- Motion Detection -- Tracking -- Optical Flow Three-Dimensional Interpretation. 330 $aThis book presents a unified view of image motion analysis under the variational framework. Variational methods, rooted in physics and mechanics, but appearing in many other domains, such as statistics, control, and computer vision, address a problem from an optimization standpoint, i.e., they formulate it as the optimization of an objective function or functional. The methods of image motion analysis described in this book use the calculus of variations to minimize (or maximize) an objective functional which transcribes all of the constraints that characterize the desired motion variables. The book addresses the four core subjects of motion analysis: Motion estimation, detection, tracking, and three-dimensional interpretation. Each topic is covered in a dedicated chapter. The presentation is prefaced by an introductory chapter which discusses the purpose of motion analysis. Further, a chapter is included which gives the basic tools and formulae related to curvature, Euler Lagrange equations, unconstrained descent optimization, and level sets, that the variational image motion processing methods use repeatedly in the book. 410 0$aSpringer topics in signal processing ;$vvolume 10. 606 $aImage analysis$xMathematical models 606 $aComputer vision 615 0$aImage analysis$xMathematical models. 615 0$aComputer vision. 676 $a621.3993 700 $aMitiche$b Amar$4aut$4http://id.loc.gov/vocabulary/relators/aut$0861058 702 $aAggarwal$b J. K$g(Jagdishkumar Keshoram),$f1936- 801 0$bMiFhGG 801 1$bMiFhGG 906 $aBOOK 912 $a9910299492303321 996 $aComputer Vision Analysis of Image Motion by Variational Methods$91921645 997 $aUNINA