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008			231227s2024 sz | o |||| 0|eng d
020			_a9783031345074
024	7		_a10.1007/978-3-031-34507-4 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTA1634 _b2024 EB
100	1		_aFusiello, Andrea _eautor _0(orcid)0000-0003-2963-0316 _1https://orcid.org/0000-0003-2963-0316 _4aut _4http://id.loc.gov/vocabulary/relators/aut _9670742
245	1	0	_aComputer Vision Three-dimensional Reconstruction Techniques _cby Andrea Fusiello
250			_afirst edition 2024
264		1	_aCham _c2024 _bSpringer International Publishing
300			_a1 recurso en línea
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_atext file _bPDF
505	0		_aForeword -- Preface -- Acknowledgements -- Introduction -- Fundamentals of Imaging -- The Pinhole Camera Model -- Camera Calibration -- Absolute and Exterior Orientation -- Two-view Geometry -- Relative Orientation -- Reconstruction from Two Images -- Nonlinear Regression -- Stereopsis: geometry -- Stereopsis: matching -- Renge Sensors -- Multiview Euclidean Reconstruction -- 3D Registration -- Multiview Projective Reconstruction and Autocalibration -- Multi-View Stereo Reconstruction -- Image-based Rendering -- A Notions of linear algebra -- B Matrix Differential Calculation -- C Regression -- D Notions of Projective Geometry -- D Math Lab code -- Index.
520			_aFrom facial recognition to self-driving cars, the applications of computer vision are vast and ever-expanding. Geometry plays a fundamental role in this discipline, providing the necessary mathematical framework to understand the underlying principles of how we perceive and interpret visual information in the world around us. This text explores the theories and computational techniques used to determine the geometric properties of solid objects through images. It covers the basic concepts and provides the necessary mathematical background for more advanced studies. The book is divided into clear and concise chapters covering a wide range of topics including image formation, camera models, feature detection and 3D reconstruction. Each chapter includes detailed explanations of the theory as well as practical examples to help the reader understand and apply the concepts presented. The book has been written with the intention of being used as a primary resource for students on university courses in computer vision, particularly final year undergraduate or postgraduate computer science or engineering courses. It is also useful for self-study and for those who, outside the academic field, find themselves applying computer vision to solve practical problems. The aim of the book is to strike a balance between the complexity of the theory and its practical applicability in terms of implementation. Rather than providing a comprehensive overview of the current state of the art, it offers a selection of specific methods with enough detail to enable the reader to implement them.
988			_aSpringer_Computer_2024
650		7	_2embne _9159793 _aVisión por ordenador
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-34507-4 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b01/2024 _dz _ejc _zSI