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All Weather Robot Vision

  • Book
  • © 2022

Overview

Authors:
  1. Jiandong Tian

    1. State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China

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  • Concentrates on robot vision in outdoor dynamic illumination and weather conditions,
  • Includes new fundamental models for illumination and scattering, which build a bridge
  • Presents numerous state-of-the-art algorithms for e.g. detecting and removing shadow

Part of the book series: Research on Intelligent Manufacturing (REINMA)

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Table of contents (10 chapters)

  1. Front Matter

    Pages i-x
    Download chapter PDF

  2. Introduction

    • Jiandong Tian
    Pages 1-27

  3. Spectral Power Distributions and Reflectance Calculations for Robot Vision

    • Jiandong Tian
    Pages 29-53

  4. Imaging Modeling and Camera Sensitivity Recovery

    • Jiandong Tian
    Pages 55-75

  5. Shadow Modeling and Detection

    • Jiandong Tian
    Pages 77-119

  6. Intrinsic-Image Deriving and Decomposition

    • Jiandong Tian
    Pages 121-154

  7. Shadow and Highlight Removal

    • Jiandong Tian
    Pages 155-187

  8. Rain and Snow Removal

    • Jiandong Tian
    Pages 189-227

  9. Single-Image Dehazing

    • Jiandong Tian
    Pages 229-270

  10. Underwater Descattering from Light Field

    • Jiandong Tian
    Pages 271-287

  11. Applications and Future Work

    • Jiandong Tian
    Pages 289-311
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Keywords

About this book

Complex illumination and meteorological conditions can significantly limit the robustness of robotic vision systems. This book focuses on image pre-processing for robot vision in complex illumination and dynamic weather conditions. It systematically covers cutting-edge models and algorithms, approaching them from a novel viewpoint based on studying the atmospheric physics and imaging mechanism. It provides valuable insights and practical methods such as illumination calculations, scattering modeling, shadow/highlight detection and removal, intrinsic image derivation, and rain/snow/fog removal technologies that will enable robots to be effective in diverse lighting and weather conditions, i.e., ensure their all-weather operating capacity. As such, the book offers a valuable resource for researchers, graduate students and engineers in the fields of robot engineering and computer science.    

Authors and Affiliations

  • State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China

    Jiandong Tian

About the author

Dr. Jiandong Tian received his B.S. degree in the department of automation, Heilongjiang University, P. R. China, in 2005. In 2011 he received his doctoral degree in Pattern Recognition and Intelligent Systems from Shenyang Institute of Automation, Chinese Academy of Sciences. Currently he is a professor in State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences. During 2015.6-2016.6, he was a Visiting Professor at Center for Visual Computing, University of California, San Diego. His research interests include robot vision, illumination modeling, and image/video processing. He has published more than 50 papers in this field. Fairly amount of them have been published in well-known journals and top conferences in computer/robot vision. Dr. Tian gained the first prize of natural science award of Chinese Association of Automation in 2019 and the first prize of natural science award of Liaoning Province in 2020, respectively.

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