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Herausgeber: 
  • Aman Behal
  • Yu Sun
  • Chi-Kit Ronald Chung
  • New Development in Robot Vision 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  September 2016  
    Genre:  Naturwissensch., Medizin, Technik 
     
    Artificial Intelligence / Automation / B / Computer Vision / Control, Robotics, Automation / engineering / Image Processing and Computer Vision / Künstliche Intelligenz
    ISBN:  9783662522738 
    EAN-Code: 
    9783662522738 
    Verlag:  Springer EN 
    Einband:  Kartoniert  
    Sprache:  English  
    Serie:  #23 - Cognitive Systems Monographs  
    Dimensionen:  H 235 mm / B 155 mm / D  
    Gewicht:  3401 gr 
    Seiten:  199 
    Illustration:  XVIII, 199 p. 106 illus., 84 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    The 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.

     

      



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