000			03037nam a22004335i 4500
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007			cr nn 008mamaa
008			220601s2017 sz | s |||| 0|eng d
020			_a9783031018183
024	7		_a10.1007/978-3-031-01818-3 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTA1634 _b2017 EB
100	1		_aChin, Tat-Jun _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686979
245	1	4	_aThe Maximum Consensus Problem : _bRecent Algorithmic Advances _cby Tat-Jun Chin, David Suter
250			_a1st edition 2017
264		1	_aCham _bSpringer International Publishing _c2017
300			_a1 recurso en línea (XV, 178 páginas)
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSynthesis Lectures on Computer Vision _x2153-1064
505	0		_aPreface -- Acknowledgments -- The Maximum Consensus Problem -- Approximate Algorithms -- Exact Algorithms -- Preprocessing for Maximum Consensus -- Appendix -- Bibliography -- Authors' Biographies -- Index .
520			_aOutlier-contaminated data is a fact of life in computer vision. For computer vision applications to perform reliably and accurately in practical settings, the processing of the input data must be conducted in a robust manner. In this context, the maximum consensus robust criterion plays a critical role by allowing the quantity of interest to be estimated from noisy and outlier-prone visual measurements. The maximum consensus problem refers to the problem of optimizing the quantity of interest according to the maximum consensus criterion. This book provides an overview of the algorithms for performing this optimization. The emphasis is on the basic operation or "inner workings" of the algorithms, and on their mathematical characteristics in terms of optimality and efficiency. The applicability of the techniques to common computer vision tasks is also highlighted. By collecting existing techniques in a single article, this book aims to trigger further developments in this theoretically interesting and practically important area.
988			_aSynthesis Collection of Technology_2017
650		7	_2embne _9145705 _aOptimización matemática
650		7	_2embne _9159793 _aVisión por ordenador _xModelos matemáticos
650		7	_2embne _9141162 _aAlgoritmos
700	1		_aSuter, David _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686980 _c(Computer scientist)
776	0	8	_iPrinted edition: _z9783031006906
776	0	8	_iPrinted edition: _z9783031029462
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-01818-3 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b02/2023 _dz _esc _zSI