000 03253nam a22005535i 4500
001 978-3-319-53508-1
003 DE-He213
005 20220801222013.0
007 cr nn 008mamaa
008 170314s2017 sz | s |||| 0|eng d
020 _a9783319535081
_9978-3-319-53508-1
024 7 _a10.1007/978-3-319-53508-1
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aTEC009000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
100 1 _aLast, Carsten.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_959170
245 1 0 _aFrom Global to Local Statistical Shape Priors
_h[electronic resource] :
_bNovel Methods to Obtain Accurate Reconstruction Results with a Limited Amount of Training Shapes /
_cby Carsten Last.
250 _a1st ed. 2017.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2017.
300 _aXXI, 259 p. 84 illus., 64 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Systems, Decision and Control,
_x2198-4190 ;
_v98
505 0 _aBasics -- Statistical Shape Models (SSMs) -- A Locally Deformable Statistical Shape Model (LDSSM) -- Evaluation of the Locally Deformable Statistical Shape Model -- Global-To-Local Shape Priors for Variational Level Set Methods -- Evaluation of the Global-To-Local Variational Formulation -- Conclusion and Outlook.
520 _aThis book proposes a new approach to handle the problem of limited training data. Common approaches to cope with this problem are to model the shape variability independently across predefined segments or to allow artificial shape variations that cannot be explained through the training data, both of which have their drawbacks. The approach presented uses a local shape prior in each element of the underlying data domain and couples all local shape priors via smoothness constraints. The book provides a sound mathematical foundation in order to embed this new shape prior formulation into the well-known variational image segmentation framework. The new segmentation approach so obtained allows accurate reconstruction of even complex object classes with only a few training shapes at hand.
650 0 _aComputational intelligence.
_97716
650 0 _aArtificial intelligence.
_93407
650 0 _aImage processing—Digital techniques.
_931565
650 0 _aComputer vision.
_959171
650 1 4 _aComputational Intelligence.
_97716
650 2 4 _aArtificial Intelligence.
_93407
650 2 4 _aComputer Imaging, Vision, Pattern Recognition and Graphics.
_931569
710 2 _aSpringerLink (Online service)
_959172
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319535074
776 0 8 _iPrinted edition:
_z9783319535098
776 0 8 _iPrinted edition:
_z9783319851693
830 0 _aStudies in Systems, Decision and Control,
_x2198-4190 ;
_v98
_959173
856 4 0 _uhttps://doi.org/10.1007/978-3-319-53508-1
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
999 _c80294
_d80294