000			04138nam a22004095i 4500
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003			DE-He213
005			20230102113133.0
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007			cr nn 008mamaa
008			140926s2015 gw | s |||| 0|eng d
020			_a9783662438596
024	7		_a10.1007/978-3-662-43859-6 _2doi
040			_bspa _dES-MaUEC
050		4	_aTJ211.3 _b2015 EB
245	1	0	_aNew Development in Robot Vision _cedited by Yu Sun, Aman Behal, Chi-Kit Ronald Chung.
264		1	_aBerlin, Heidelberg _bSpringer International Publishing _c2015
300			_a1 recurso en línea (XVIII, 199 páginas 106 ilustraciones, 84 ilustraciones a color.)
336			_2rdacontent _aTexto (visual) _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
490	0		_aCognitive Systems Monographs, _x1867-4925 ; _v23
490	0		_aEngineering (Springer-11647)
505	0		_aIntensity-Difference Based Monocular Visual Odometry for Planetary Rovers -- Incremental Light Bundle Adjustment: Probabilistic Analysis and Application to Robotic Navigation -- Online Learning of Vision-Based Robot Control during Autonomous Operation -- Semantic and Spatial Content Fusion for Scene Recognition -- Modeling paired objects and their interaction -- Multi-modal Manhattan World Structure Estimation for Domestic Robots -- Improving RGB-D Scene Reconstruction Using Rolling Shutter Rectification -- RMSD: A 3D Real-time Mid-Level Scene Description System -- Probabilistic Active Recognition of Multiple Objects using Hough-based Geometric Matching Features.
520	3		_aThe field of robotic vision has advanced dramatically recently with the development of new range sensors.  Tremendous progress has been made resulting in significant impact on areas such as robotic navigation, scene/environment understanding, and visual learning. This edited book provides a solid and diversified reference source for some of the most recent important advancements in the field of robotic vision. The book starts with articles that describe new techniques to understand scenes from 2D/3D data such as estimation of planar structures, recognition of multiple objects in the scene using different kinds of features as well as their spatial and semantic relationships, generation of 3D object models, approach to recognize partially occluded objects, etc. Novel techniques are introduced to improve 3D perception accuracy with other sensors such as a gyroscope, positioning accuracy with a visual servoing based alignment strategy for microassembly, and increasing object recognition reliability using related manipulation motion models. For autonomous robot navigation, different vision-based localization and tracking strategies and algorithms are discussed. New approaches using probabilistic analysis for robot navigation, online learning of vision-based robot control, and 3D motion estimation via intensity differences from a monocular camera are described. This collection will be beneficial to graduate students, researchers, and professionals working in the area of robotic vision.  .
988			_aEBSPRINGER_2018
650		7	_9668436 _aVisión artificial (Robótica)
700	1		_aSun, Yu. _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt _0http://id.loc.gov/authorities/names/n80062154 _1http://viaf.org/viaf/29537230/ _1http://dbpedia.org/resource/Hyunpung_High_School_FC__Kim_Yu-Sun__1 _997606
700	1		_aBehal, Aman. _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt _0http://id.loc.gov/authorities/names/n2009065910 _1http://viaf.org/viaf/162956658/
700	1		_aChung, Chi-Kit Ronald. _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
776	0	8	_iEdición impresa: _z9783662438602
776	0	8	_iEdición impresa: _z9783662438589
776	0	8	_iEdición impresa: _z9783662522738
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-662-43859-6 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b03/2019 _dz _eIG _zSI