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007 cr nn 008mamaa
008 121227s2004 gw | s |||| 0|eng d
020 _a9783540246565
_9978-3-540-24656-5
024 7 _a10.1007/b97201
_2doi
050 4 _aQA440-699
072 7 _aPBM
_2bicssc
072 7 _aMAT012000
_2bisacsh
072 7 _aPBM
_2thema
082 0 4 _a516
_223
100 1 _aHeuel, Stephan.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aUncertain Projective Geometry
_h[electronic resource] :
_bStatistical Reasoning for Polyhedral Object Reconstruction /
_cby Stephan Heuel.
250 _a1st ed. 2004.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2004.
300 _aXVIII, 210 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Computer Science,
_x1611-3349 ;
_v3008
505 0 _a1 Introduction -- 2 Representation of Geometric Entities and Transformations -- 3 Geometric Reasoning Using Projective Geometry -- 4 Statistical Geometric Reasoning -- 5 Polyhedral Object Reconstruction -- 6 Conclusions -- A Notation -- B Linear Algebra -- C Statistics.
520 _aAlgebraic projective geometry, with its multilinear relations and its embedding into Grassmann-Cayley algebra, has become the basic representation of multiple view geometry, resulting in deep insights into the algebraic structure of geometric relations, as well as in efficient and versatile algorithms for computer vision and image analysis. This book provides a coherent integration of algebraic projective geometry and spatial reasoning under uncertainty with applications in computer vision. Beyond systematically introducing the theoretical foundations from geometry and statistics and clear rules for performing geometric reasoning under uncertainty, the author provides a collection of detailed algorithms. The book addresses researchers and advanced students interested in algebraic projective geometry for image analysis, in statistical representation of objects and transformations, or in generic tools for testing and estimating within the context of geometric multiple-view analysis.
650 0 _aGeometry.
650 0 _aPattern recognition systems.
650 0 _aComputer vision.
650 0 _aComputer science
_xMathematics.
650 0 _aMathematical statistics.
650 0 _aComputer graphics.
650 0 _aArtificial intelligence.
650 1 4 _aGeometry.
650 2 4 _aAutomated Pattern Recognition.
650 2 4 _aComputer Vision.
650 2 4 _aProbability and Statistics in Computer Science.
650 2 4 _aComputer Graphics.
650 2 4 _aArtificial Intelligence.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783540220299
776 0 8 _iPrinted edition:
_z9783662207802
830 0 _aLecture Notes in Computer Science,
_x1611-3349 ;
_v3008
856 4 0 _uhttps://doi.org/10.1007/b97201
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
912 _aZDB-2-LNC
912 _aZDB-2-BAE
942 _cSPRINGER
999 _c186354
_d186354