000			03463nam a22004455i 4500
001			978-0-85729-965-9
003			DE-He213
005			20251006084447.0
007			cr nn 008mamaa
008			110815s2011 xxk| s |||| 0|eng d
020			_a9780857299659
020			_a99780857299659
024	7		_a10.1007/978-0-85729-965-9 _2doi
082	0	4	_a006.6 _223
082	0	4	_a006.37 _223
100	1		_aWedel, Andreas. _eauthor.
245	1	0	_aStereo Scene Flow for 3D Motion Analysis _h[electronic resource] / _cby Andreas Wedel, Daniel Cremers.
264		1	_aLondon : _bSpringer London, _c2011.
300			_aIX, 128p. 74 illus., 60 illus. in color. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aMachine Vision Systems -- Optical Flow Estimation -- Residual Images and Optical Flow Results -- Scene Flow -- Motion Metrics for Scene Flow -- Extensions of Scene Flow -- Conclusion and Outlook.
520			_aThe accurate and precise estimation of three-dimensional motion vector fields in real time remains one of the key targets for the discipline of computer vision. This important text/reference presents methods for estimating optical flow and scene flow motion with high accuracy, focusing on the practical application of these methods in camera-based driver assistance systems. Clearly and logically structured, the book builds from basic themes to more advanced concepts, covering topics from variational methods and optic flow estimation, to adaptive regularization and scene flow analysis. This in-depth discussion culminates in the development of a novel, accurate and robust scene flow method for the higher-level challenges posed by real-world applications. Topics and features: Reviews the major advances in motion estimation and motion analysis, and the latest progress of dense optical flow algorithms Investigates the use of residual images for optical flow Examines methods for deriving motion from stereo image sequences Analyses the error characteristics for motion variables, and derives scene flow metrics for movement likelihood and velocity Introduces a framework for scene flow-based moving object detection and segmentation, and discusses the application of Kalman filters for propagating scene flow estimation over time Includes pseudo code for all important computational challenges Contains Appendices on data terms and quadratic optimization, and scene flow implementation using Euler-Lagrange equations, in addition to a helpful Glossary and Index A valuable reference for researchers and graduate students on segmentation, optical flow and scene flow, this unique book will also be of great interest to professionals involved in the development of driver assistance systems.
650		0	_aCOMPUTER SCIENCE.
650		0	_aCOMPUTER VISION.
650		0	_aOPTICAL PATTERN RECOGNITION.
650	1	4	_aCOMPUTER SCIENCE.
650	2	4	_aIMAGE PROCESSING AND COMPUTER VISION.
650	2	4	_aPATTERN RECOGNITION.
700	1		_aCremers, Daniel. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780857299642
856	4	0	_uhttp://dx.doi.org/10.1007/978-0-85729-965-9 _zVer el texto completo en las instalaciones del CICY
912			_aZDB-2-SCS
942			_2ddc _cER
999			_c60182 _d60182