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008			220601s2013 sz | o |||| 0|eng d
020			_a9783031015205
024	7		_a10.1007/978-3-031-01520-5 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTA1637 _b2013 EB
100	1		_aZwart, Christine M. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686106
245	1	0	_aControl Grid Motion Estimation for Efficient Application of Optical Flow _cby Christine M. Zwart, David Frakes
250			_a1st edition 2013
264		1	_aCham _bSpringer International Publishing _c2013
300			_a1 recurso en línea (VIII, 79 páginas)
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSynthesis Lectures on Algorithms and Software in Engineering _x1938-1735
505	0		_aIntroduction -- Control Grid Interpolation (CGI) -- Application of CGI to Registration Problems -- Application of CGI to Interpolation Problems -- Discussion and Conclusions.
520			_aMotion estimation is a long-standing cornerstone of image and video processing. Most notably, motion estimation serves as the foundation for many of today's ubiquitous video coding standards including H.264. Motion estimators also play key roles in countless other applications that serve the consumer, industrial, biomedical, and military sectors. Of the many available motion estimation techniques, optical flow is widely regarded as most flexible. The flexibility offered by optical flow is particularly useful for complex registration and interpolation problems, but comes at a considerable computational expense. As the volume and dimensionality of data that motion estimators are applied to continue to grow, that expense becomes more and more costly. Control grid motion estimators based on optical flow can accomplish motion estimation with flexibility similar to pure optical flow, but at a fraction of the computational expense. Control grid methods also offer the added benefit of representing motion far more compactly than pure optical flow. This booklet explores control grid motion estimation and provides implementations of the approach that apply to data of multiple dimensionalities. Important current applications of control grid methods including registration and interpolation are also developed. Table of Contents: Introduction / Control Grid Interpolation (CGI) / Application of CGI to Registration Problems / Application of CGI to Interpolation Problems / Discussion and Conclusions.
988			_aSynthesis Collection of Technology_2013
650		7	_2embne _9413188 _aProceso digital de imágenes
700	1		_aFrakes, David H. _d1976- _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686107 _q(David Harold)
776	0	8	_iPrinted edition: _z9783031003929
776	0	8	_iPrinted edition: _z9783031026485
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-01520-5 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b01/2023 _dz _eb _zSI