000 04030nam a22005535i 4500
001 978-3-662-43859-6
003 DE-He213
005 20200421111157.0
007 cr nn 008mamaa
008 140926s2015 gw | s |||| 0|eng d
020 _a9783662438596
_9978-3-662-43859-6
024 7 _a10.1007/978-3-662-43859-6
_2doi
050 4 _aTJ210.2-211.495
050 4 _aT59.5
072 7 _aTJFM1
_2bicssc
072 7 _aTEC037000
_2bisacsh
072 7 _aTEC004000
_2bisacsh
082 0 4 _a629.892
_223
245 1 0 _aNew Development in Robot Vision
_h[electronic resource] /
_cedited by Yu Sun, Aman Behal, Chi-Kit Ronald Chung.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2015.
300 _aXVIII, 199 p. 106 illus., 84 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aCognitive Systems Monographs,
_x1867-4925 ;
_v23
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 _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.  .
650 0 _aEngineering.
650 0 _aArtificial intelligence.
650 0 _aImage processing.
650 0 _aRobotics.
650 0 _aAutomation.
650 1 4 _aEngineering.
650 2 4 _aRobotics and Automation.
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _aImage Processing and Computer Vision.
700 1 _aSun, Yu.
_eeditor.
700 1 _aBehal, Aman.
_eeditor.
700 1 _aChung, Chi-Kit Ronald.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783662438589
830 0 _aCognitive Systems Monographs,
_x1867-4925 ;
_v23
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-662-43859-6
912 _aZDB-2-ENG
942 _cEBK
999 _c53584
_d53584