LEADER 04002nam 2200661 a 450 001 9910453403703321 005 20200520144314.0 010 $a1-281-95485-3 010 $a9786611954857 010 $a1-84800-138-X 024 7 $a10.1007/978-1-84800-138-1 035 $a(CKB)1000000000545908 035 $a(EBL)417000 035 $a(SSID)ssj0000310314 035 $a(PQKBManifestationID)11214147 035 $a(PQKBTitleCode)TC0000310314 035 $a(PQKBWorkID)10288975 035 $a(PQKB)11032367 035 $a(DE-He213)978-1-84800-138-1 035 $a(MiAaPQ)EBC417000 035 $a(PPN)132863642 035 $a(Au-PeEL)EBL417000 035 $a(CaPaEBR)ebr10274990 035 $a(CaONFJC)MIL195485 035 $a(OCoLC)317883794 035 $a(EXLCZ)991000000000545908 100 $a20080716d2008 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aStatistical models of shape$b[electronic resource] $eoptimisation and evaluation /$fRhodri H. Davies, Carole Twining, Chris Taylor 205 $a1st ed. 2008. 210 $aLondon $cSpringer$dc2008 215 $a1 online resource (308 p.) 300 $aDescription based upon print version of record. 311 $a1-4471-6042-8 311 $a1-84800-137-1 320 $aIncludes bibliographical references (p. 285-302) and index. 327 $aStatistical Models of Shape and Appearance -- Establishing Correspondence -- Objective Functions -- Re-parameterisation of Open and Closed Curves -- Parameterisation and Re-parameterisation of Surfaces -- Optimisation -- Non-parametric Regularization -- Evaluation of Statistical Models. 330 $aStatistical models of shape, learnt from a set of examples, are a widely-used tool in image interpretation and shape analysis. Integral to this learning process is the establishment of a dense groupwise correspondence across the set of training examples. This book gives a comprehensive and up-to-date account of the optimisation approach to shape correspondence, and the question of evaluating the quality of the resulting model in the absence of ground-truth data. It begins with a complete account of the basics of statistical shape models, for both finite and infinite-dimensional representations of shape, and includes linear, non-linear, and kernel-based approaches to modelling distributions of shapes. The optimisation approach is then developed, with a detailed discussion of the various objective functions available for establishing correspondence, and a particular focus on the Minimum Description Length approach. Various methods for the manipulation of correspondence for shape curves and surfaces are dealt with in detail, including recent advances such as the application of fluid-based methods. This complete and self-contained account of the subject area brings together results from a fifteen-year program of research and development. It includes proofs of many of the basic results, as well as mathematical appendices covering areas which may not be totally familiar to some readers. Comprehensive implementation details are also included, along with extensive pseudo-code for the main algorithms. Graduate students, researchers, teachers, and professionals involved in either the development or the usage of statistical shape models will find this an essential resource. 606 $aShape theory (Topology)$xStatistical methods 606 $aMathematical optimization 608 $aElectronic books. 615 0$aShape theory (Topology)$xStatistical methods. 615 0$aMathematical optimization. 676 $a514.24 700 $aDavies$b Rhodri$0877783 701 $aTwining$b Carole$0877784 701 $aTaylor$b Chris$g(Christopher J.)$0861121 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910453403703321 996 $aStatistical models of shape$91959880 997 $aUNINA