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Robotic Vision

Book Description

Robotic systems consist of object or scene recognition, vision-based motion control, vision-based mapping, and dense range sensing, and are used for identification and navigation. As these computer vision and robotic connections continue to develop, the benefits of vision technology including savings, improved quality, reliability, safety, and productivity are revealed.

Robotic Vision: Technologies for Machine Learning and Vision Applications is a comprehensive collection which highlights a solid framework for understanding existing work and planning future research. This book includes current research on the fields of robotics, machine vision, image processing and pattern recognition that is important to applying machine vision methods in the real world.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Editorial Advisory Board and List of Reviewers
    1. List of Reviewers
  5. Foreword
  6. Preface
    1. SECTION 1: COMPUTER VISION
    2. SECTION 2: COMPUTER VISION APPLICATIONS
    3. SECTION 3: 3D COMPUTER VISION AND ROBOTICS
    4. SECTION 4: SOCIAL ROBOTICS
    5. SECTION 5: VISION CONTROL
    6. SECTION 6: VISUAL ATTENTION
  7. Acknowledgment
  8. Section 1: Computer Vision
    1. Chapter 1: Face Recognition with Active Appearance Model (AAM)
      1. ABSTRACT
      2. INTRODUCTION
      3. UNDERSTANDING FACE RECOGNITION PROCESS
      4. CLASSIFIER BASED ON ACTIVE APPEARANCE MODEL
      5. APPLICATIONS AND TOOLS
      6. FUTURE RESEARCH DIRECTIONS
      7. CONCLUSION
    2. Chapter 2: Uniform Sampling of Rotations for Discrete and Continuous Learning of 2D Shape Models
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. UNIFORM ROTATIONS
      5. SOLUTIONS AND RECOMMENDATIONS
      6. FUTURE RESEARCH DIRECTIONS
      7. CONCLUSION
    3. Chapter 3: Comparative Analysis of Temporal Segmentation Methods of Video Sequences
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. SEGMENTATION OF VIDEO SEQUENCES
      5. FUTURE RESEARCH DIRECTIONS
      6. CONCLUSION
  9. Section 2: Computer Vision Applications
    1. Chapter 4: Security Applications Using Computer Vision
      1. ABSTRACT
      2. INTRODUCTION
      3. ARCHITECTURE AND SIMULATION RESULTS
      4. CONCLUSION
    2. Chapter 5: Visual Detection in Linked Multi-Component Robotic Systems
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. ROBOTIC VISION SYSTEM
      5. FUTURE RESEARCH DIRECTIONS
      6. CONCLUSION
    3. Chapter 6: Building a Multiple Object Tracking System with Occlusion Handling in Surveillance Videos
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. MAIN FOCUS OF THE CHAPTER
      5. FUTURE RESEARCH DIRECTIONS
      6. CONCLUSION
    4. Chapter 7: A Robust Color Watershed Transformation and Image Segmentation Defined on RGB Spherical Coordinates
      1. ABSTRACT
      2. INTRODUCTION
      3. SPHERICAL COORDINATES IN THE RGB COLOR SPACE
      4. GRADIENTS
      5. COLOR IMAGE SEGMENTATION
      6. EXPERIMENTAL RESULTS
      7. CONCLUSION
    5. Chapter 8: Computer Vision Applications of Self-Organizing Neural Networks
      1. ABSTRACT
      2. INTRODUCTION
      3. TOPOLOGY LEARNING
      4. EXAMPLES
      5. FUTURE RESEARCH DIRECTIONS
      6. CONCLUSION
  10. Section 3: 3D Computer Vision and Robotics
    1. Chapter 9: A Review of Registration Methods on Mobile Robots
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. 2D/3D DATA ACQUISITION
      5. EXPERIMENTATION
      6. FUTURE RESEARCH DIRECTIONS
      7. CONCLUSION
    2. Chapter 10: Methodologies for Evaluating Disparity Estimation Algorithms
      1. ABSTRACT
      2. INTRODUCTION
      3. STATE-OF-THE-ART
      4. COMPONENTS OF AN EVALUATION METHODOLOGY
      5. DRAWBACKS AND ADVANTAGES OF EXISTING EVALUATION METHODOLOGIES
      6. FINAL REMARKS
    3. Chapter 11: Real-Time Structure Estimation in Dynamic Scenes Using a Single Camera
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. STRUCTURE ESTIMATION OF A MOVING OBJECT
      5. UNKNOWN INPUT OBSERVER FOR STRUCTURE ESTIMATION
      6. EXPERIMENTS
      7. FUTURE RESEARCH DIRECTIONS
      8. CONCLUSION
    4. Chapter 12: Intelligent Stereo Vision in Autonomous Robot Traversability Estimation
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. STEREO VISION FOR AUTONOMOUS ROBOTS
      5. FUZZY OBSTACLE ANALYSIS
      6. V-DISPARITY FEATURE EXTRACTION AND SVM-BASED LEARNING
      7. CONCLUSION AND DISCUSSION
  11. Section 4: Social Robotics
    1. Chapter 13: Gesture Learning by Imitation Architecture for a Social Robot
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. MAIN FOCUS OF THE CHAPTER
      5. FUTURE RESEARCH DIRECTIONS
      6. CONCLUSION
    2. Chapter 14: Computer Vision for Learning to Interact Socially with Humans
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. ROBOTIC ARCHITECTURE
      5. EXPERIMENTAL RESULTS
      6. FUTURE RESEARCH DIRECTIONS
      7. CONCLUSION
    3. Chapter 15: Learning Robot Vision for Assisted Living
      1. ABSTRACT
      2. INTRODUCTION
      3. RELATED WORKS
      4. METHODS
      5. CASE STUDY
      6. CONCLUSION AND FUTURE RESEARCH DIRECTIONS
    4. Chapter 16: An Integrated Framework for Robust Human-Robot Interaction
      1. ABSTRACT
      2. INTRODUCTION
      3. RELATED WORK
      4. INTEGRATED FRAMEWORK FOR HRI
      5. CONCLUSION AND FUTURE RESEARCH DIRECTIONS
  12. Section 5: Vision Control
    1. Chapter 17: Collaborative Exploration Based on Simultaneous Localization and Mapping
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. MULTI-ROBOT EXPLORATION: ASSIGNMENT OF ROBOTS TO REGIONS
      5. CONCLUSION AND FUTURE RESEARCH
    2. Chapter 18: An Embedded Vision System for RoboCup
      1. ABSTRACT
      2. INTRODUCTION
      3. ARCHITECTURE AND VISION MODULE
      4. WORLD OBJECTS RECOGNITION AND FEATURES DETECTION
      5. KNOWLEDGE EXTRACTION
      6. EXPERIMENTAL RESULTS
      7. CONCLUSION
    3. Chapter 19: Visual Control of an Autonomous Indoor Robotic Blimp
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. BLIMP EXTRACTION
      5. BLIMP’S VISUAL ODOMETRY
      6. VISUAL SERVOING CONTROLLER
      7. FUTURE RESEARCH DIRECTIONS
      8. CONCLUSION
  13. Section 6: Visual Attention
    1. Chapter 20: Selective Review of Visual Attention Models
      1. ABSTRACT
      2. VISUAL ATTENTION
      3. ATTENTION MODELS
      4. VISUAL ATTENTION MODEL FOR ROBOT CONTROL
    2. Chapter 21: Attentive Visual Memory for Robot Localization
      1. ABSTRACT
      2. INTRODUCTION
      3. RELATED WORKS
      4. DESIGN
      5. LOCAL VISUAL MEMORY
      6. VISUAL ATTENTION
      7. EVOLUTIONARY VISUAL LOCALIZATION
      8. EXPERIMENTS
      9. CONCLUSION
    3. Chapter 22: Artificial Visual Attention Using Combinatorial Pyramids
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. THE PROPOSED ARTIFICIAL MODEL OF ATTENTION
      5. RECOGNITION STAGE
      6. FUTURE RESEARCH DIRECTIONS
      7. CONCLUSION
  14. Compilation of References
  15. About the Contributors