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008			230211s2011 sz | s |||| 0|eng d
020			_a9783031015533
024	7		_a10.1007/978-3-031-01553-3 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTA1634 _b2011 EB
100	1		_aGrauman, Kristen Lorraine, _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686721 _d1979-
245	1	0	_aVisual Object Recognition _cby Kristen Grauman, Bastian Leibe
250			_a1st edition 2011
264		1	_aCham _bSpringer International Publishing _c2011
300			_a1 recurso en línea (XVII, 163 páginas)
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSynthesis Lectures on Artificial Intelligence and Machine Learning _x1939-4616
505	0		_aIntroduction -- Overview: Recognition of Specific Objects -- Local Features: Detection and Description -- Matching Local Features -- Geometric Verification of Matched Features -- Example Systems: Specific-Object Recognition -- Overview: Recognition of Generic Object Categories -- Representations for Object Categories -- Generic Object Detection: Finding and Scoring Candidates -- Learning Generic Object Category Models -- Example Systems: Generic Object Recognition -- Other Considerations and Current Challenges -- Conclusions.
520			_aThe visual recognition problem is central to computer vision research. From robotics to information retrieval, many desired applications demand the ability to identify and localize categories, places, and objects. This tutorial overviews computer vision algorithms for visual object recognition and image classification. We introduce primary representations and learning approaches, with an emphasis on recent advances in the field. The target audience consists of researchers or students working in AI, robotics, or vision who would like to understand what methods and representations are available for these problems. This lecture summarizes what is and isn't possible to do reliably today, and overviews key concepts that could be employed in systems requiring visual categorization. Table of Contents: Introduction / Overview: Recognition of Specific Objects / Local Features: Detection and Description / Matching Local Features / Geometric Verification of Matched Features / Example Systems: Specific-Object Recognition / Overview: Recognition of Generic Object Categories / Representations for Object Categories / Generic Object Detection: Finding and Scoring Candidates / Learning Generic Object Category Models / Example Systems: Generic Object Recognition / Other Considerations and Current Challenges / Conclusions.
988			_aSynthesis Collection of Technology_2011
650		7	_2embne _9159793 _aVisión por ordenador
650		7	_2embne _9152614 _aReconocimiento de formas
700	1		_aLeibe, Bastian _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686722
776	0	8	_iPrinted edition: _z9783031004254
776	0	8	_iPrinted edition: _z9783031026812
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-01553-3 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b02/2023 _dz _eIG _zSI