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Artificial Vision

Book Description

Artificial Vision is a rapidly growing discipline, aiming to build computational models of the visual functionalities in humans, as well as machines that emulate them. Visual communication in itself involves a numberof challenging topics with a dramatic impact on contemporary culture where human-computer interaction and human dialogue play a more and more significant role.
This state-of-the-art book brings together carefully selected review articles from world renowned researchers at the forefront of this exciting area. The contributions cover topics including image processing, computational geometry, optics, pattern recognition, and computer science. The book is divided into three sections. Part I covers active vision; Part II deals with the integration of visual with cognitive capabilities; and Part III concerns visual communication.
Artificial Vision will be essential reading for students and researchers in image processing, vision, and computer science who want to grasp the current concepts and future directions of this challenging field.

Key Features
* This state-of-the-art book brings together selected review articles and accounts of current projects from world-renowned researchers at the forefront of this exciting area; The contributions cover topics such as:
* psychology of perception
* image processing
* computational geometry
* visual knowledge representation and languages
* It is this truly multi-disciplinary approach that has produced successful theories and applications for the subject.

Table of Contents

  1. Cover image
  2. Title page
  3. Table of Contents
  4. Signal Processing and its Applications
  5. Copyright
  6. Series Preface
  7. About the Editors
  8. List of Contributors
  9. Preface
  10. INTRODUCTION TO ACTIVE VISION
  11. Chapter 1: Attentional Engagement in Vision Systems
    1. 1.1 INTRODUCTION
    2. 1.2 ATTENTION IN PSYCHOLOGY
    3. 1.3 ATTENTION IN NEUROSCIENCES
    4. 1.4 THE ATTENTIONAL EXECUTIVE SYSTEM
  12. Chapter 2: Attentional Mechanisms in Computer Vision
    1. 2.1 INTRODUCTION
    2. 2.2 MECHANISMS OF FOVEATION
    3. 2.3 ATTENTIONAL MECHANISMS IN COMPUTER VISION
    4. 2.4 CONCLUSIONS
  13. Chapter 3: The Active Vision Idea
    1. 3.1 WHAT IS ‘ACTIVE’?
    2. 3.2 HISTORICAL FRAME
    3. 3.3 THE RECONSTRUCTIONIST SCHOOL
    4. 3.4 ACTIVE RECONSTRUCTION
    5. 3.5 PURPOSIVE VISION
    6. 3.6 INTELLIGENT PERCEPTION AND THE ACTIVE APPROACH
    7. 3.7 ACTIVE COMPUTATIONAL VISION AND REPRESENTATIONS
    8. 3.8 CONCLUSIONS
  14. Chapter 4: Active Model Acquisition and Sensor Planning
    1. 4.1 INTRODUCTION
    2. 4.2 BACKGROUND
    3. 4.3 EXAMPLES OF IMPLEMENTED SYSTEMS
    4. ACKNOWLEDGEMENTS
  15. Chapter 5: The Regularization of Early Vision
    1. 5.1 INTRODUCTION
    2. 5.2 BASIC CONCEPTS
    3. 5.3 ILL-POSED PROBLEMS AND REGULARIZATION THEORY
    4. 5.4 EARLY VISION REVISITED
    5. 5.5 DISCUSSION
    6. 5.6 CONCLUSIONS
  16. INTRODUCTION TO INTEGRATING VISUAL MODULES
  17. Chapter 6: Geometric Modelling and Spatial Reasoning
    1. 6.1 INTRODUCTION
    2. 6.2 OBJECT REPRESENTATIONS FOR RECOGNITION
    3. 6.3 REPRESENTATION SCHEMES
    4. 6.4 REPRESENTATION ISSUES IN IMAGE UNDERSTANDING
    5. 6.5 ALGORITHMS FOR SPATIAL REASONING
    6. 6.6 CONCLUSIONS
  18. Chapter 7: Vision as Uncertain Knowledge
    1. 7.1 INTRODUCTION TO VISION AS KNOWLEDGE
    2. 7.2 PROBABILISTIC NETWORKS BASICS
    3. 7.3 PLANNING IN UNCERTAIN UNIVERSES
    4. 7.4 MODELLING SPACE STRUCTURES
    5. 7.5 VISUAL INFERENCE
    6. 7.6 PLANNING VISUAL CONTROL
    7. 7.7 CONCLUSIONS
  19. Chapter 8: Distributed Systems for Fusion of Visual Information
    1. 8.1 DISTRIBUTED SYSTEMS AND INFORMATION FUSION
    2. 8.2 FUSION OF VISUAL INFORMATION
    3. 8.3 DISTRIBUTED INFORMATION SYSTEMS
    4. 8.4 APPLICATIONS
    5. 8.5 CONCLUSIONS
  20. Chapter 9: Hybrid Computation and Reasoning for Artificial Vision
    1. 9.1 INTRODUCTION
    2. 9.2 THE DESIGN OF THE ARCHITECTURE
    3. 9.3 THE GEOMETRIC PRIMITIVES
    4. 9.4 THE SOLID MODELLING SYSTEM
    5. 9.5 FROM 2D DATA TO THE 3D GEOMETRIC REPRESENTATION OF OBJECTS
    6. 9.6 FROM THE IMAGES TO THE SHAPE
    7. 9.7 FROM THE SHAPE TO THE SUPERQUADRICS
    8. 9.8 THE CONCEPTUAL LEVEL OF REPRESENTATION
    9. 9.9 THE LINGUISTIC LEVEL
    10. 9.10 THE MAPPING BETWEEN THE CONCEPTUAL AND LINGUISTIC LEVELS
    11. 9.11 THE FOCUS-OF-ATTENTION PROCESS
    12. 9.12 THE NEURAL NETWORK IMPLEMENTATION OF THE MAPPING BETWEEN THE CONCEPTUAL AND THE LINGUISTIC LEVELS
    13. 9.13 EXPERIMENTAL RESULTS
    14. 9.14 CONCLUSIONS
    15. Appendix 9.A A Brief Description of the KL-ONE System
  21. INTRODUCTION TO VISUAL COMMUNICATION
  22. Chapter 10: Illusion and Difference
    1. 10.1 THE NATURE OF ILLUSION
    2. 10.2 THE ‘FINESTRA ALBERTIANA’ AND VIRTUAL REALITY
    3. 10.3 ABOUT THE RELATIONSHIP BETWEEN IDOL AND ICON
    4. 10.4 DUALISM BETWEEN APPEARANCE AND REALITY
    5. 10.5 BETWEEN INCLUSION AND IMMERSION
  23. Chapter 11: Computing with/on Images
    1. 11.1 INTRODUCTION
    2. 11.2 TOWARD VISUAL LANGUAGES
    3. 11.3 VISUAL SENTENCES
    4. 11.4 VISUAL LANGUAGES
    5. 11.5 A WALK THROUGH EXISTING SYSTEMS BASED ON VISUAL LANGUAGES
    6. 11.6 CONCLUSIONS
  24. Chapter 12: Visual Databases
    1. 12.1 INTRODUCTION
    2. 12.2 SINGLE IMAGES
    3. 12.3 IMAGE SEQUENCES
  25. Chapter 13: Visual Languages for Tele-action Objects
    1. 13.1 INTRODUCTION
    2. 13.2 GENERALIZED ICONS
    3. 13.3 SPATIAL TEMPORAL OPERATORS
    4. 13.4 REPRESENTATION OF MEANING FOR GENERALIZED ICONS
    5. 13.5 THE SYNTACTIC ASPECT OF MULTIDIMENSIONAL LANGUAGE FOR TELE-ACTION OBJECTS
    6. 13.6 THE DYNAMIC ASPECT OF MULTIDIMENSIONAL LANGUAGE FOR TELE-ACTION OBJECTS
    7. 13.7 THE ACTIVE INDEX AND TELE-ACTION OBJECTS
    8. 13.8 BOOKMAN – AN APPLICATION EXAMPLE
    9. 13.9 CONCLUSION
    10. ACKNOWLEDGEMENTS
  26. Index