000 | 03473nam a22005535i 4500 | ||
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001 | 978-3-030-11760-3 | ||
003 | DE-He213 | ||
005 | 20220801214505.0 | ||
007 | cr nn 008mamaa | ||
008 | 190228s2019 sz | s |||| 0|eng d | ||
020 |
_a9783030117603 _9978-3-030-11760-3 |
||
024 | 7 |
_a10.1007/978-3-030-11760-3 _2doi |
|
050 | 4 | _aG70.212-.217 | |
072 | 7 |
_aRGW _2bicssc |
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_aTEC036000 _2bisacsh |
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_aRGW _2thema |
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082 | 0 | 4 |
_a910.285 _223 |
100 | 1 |
_aCrosilla, Fabio. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _938674 |
|
245 | 1 | 0 |
_aAdvanced Procrustes Analysis Models in Photogrammetric Computer Vision _h[electronic resource] / _cby Fabio Crosilla, Alberto Beinat, Andrea Fusiello, Eleonora Maset, Domenico Visintini. |
250 | _a1st ed. 2019. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2019. |
|
300 |
_aXI, 172 p. 66 illus., 59 illus. in color. _bonline resource. |
||
336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
||
490 | 1 |
_aCISM International Centre for Mechanical Sciences, Courses and Lectures, _x2309-3706 ; _v590 |
|
505 | 0 | _aTheory of procrustes analysis models -- An introduction to computer vision and laser scanning -- Applications of procrustes analysis models. | |
520 | _aThis book gives a comprehensive view of the developed procrustes models, including the isotropic, the generalized and the anisotropic variants. These represent original tools to perform, among others, the bundle block adjustment and the global registration of multiple 3D LiDAR point clouds. Moreover, the book also reports the recently derived total least squares solution of the anisotropic Procrustes model, together with its practical application in solving the exterior orientation of one image. The book is aimed at all those interested in discovering valuable innovative algorithms for solving various photogrammetric computer vision problems. In this context, where functional models are non-linear, Procrustean methods prove to be powerful since they do not require any linearization nor approximated values of the unknown parameters, furnishing at the same time results comparable in terms of accuracy with those given by the state-of-the-art methods. | ||
650 | 0 |
_aGeographic information systems. _911535 |
|
650 | 0 |
_aComputer vision. _938675 |
|
650 | 1 | 4 |
_aGeographical Information System. _931831 |
650 | 2 | 4 |
_aComputer Vision. _938676 |
700 | 1 |
_aBeinat, Alberto. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _938677 |
|
700 | 1 |
_aFusiello, Andrea. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _938678 |
|
700 | 1 |
_aMaset, Eleonora. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _938679 |
|
700 | 1 |
_aVisintini, Domenico. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _938680 |
|
710 | 2 |
_aSpringerLink (Online service) _938681 |
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773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783030117597 |
776 | 0 | 8 |
_iPrinted edition: _z9783030117610 |
830 | 0 |
_aCISM International Centre for Mechanical Sciences, Courses and Lectures, _x2309-3706 ; _v590 _938682 |
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856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-030-11760-3 |
912 | _aZDB-2-ENG | ||
912 | _aZDB-2-SXE | ||
942 | _cEBK | ||
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