Previous: A Computational Model of Color Perception and Color Naming Up: A Computational Model of Color Perception and Color Naming Next: Introduction

Contents

• Contents
• Introduction
  • Background
  • Thesis and Scientific Contributions
• Problem Definition
  • Color Perception
  • Color Naming
  • Outline of the Model
• Wider Significance
  • Embodiment, Symbol Grounding, and Natural Language Semantics
  • Knowledge Representation and Semantics
    • Semantics as vaporware
    • Categorial misfits
  • Some Pseudo-Philosophical Notes
• Related Work
  • Embodiment and Symbol Grounding
  • Basic Color Terms
  • Neurophysiology of Color Vision
  • Color Models
    • The Munsell and Ostwald color models
    • CIE chromaticity and related models
    • RGB color models
    • Computer graphics and computer vision color models
    • Hurvich & Jameson's opponent-colors theory
    • De Valois & De Valois's color model
    • Valberg et al.'s equidistant color space
  • Models of Color Perception and Color Naming
• From Visual Stimuli to Color Space
  • General
  • Assumptions and Limitations
  • Modeling Neurophysiological Data
    • Reconstruction of 3D response functions
    • Saturation levels revisited
    • Reducing six dimensions to three
    • The sigmoid-of-linear activation model
    • Normalization of the basis functions
  • Visualizing Color Space Properties
  • Some Interesting Properties of the NPP Space
  • Psycho-Physical Variables
  • Learning a Color Space Transformation
• From Color Space to Color Names
  • The Normalized Gaussian Category Model
  • Locating the Berlin and Kay Color Stimuli in the Color Space
  • Fitting the Model to the Data
  • Theoretical Evaluation of the Category Model
  • Comparing Performance for Different Color Spaces
  • A Sketch of a Developmental Model
• Putting It All Together:
  From Visual Stimuli to Color Names, and Back
  • Naming Color Samples
    • Complex color names
  • Pointing Out Examples of Colors
  • Choosing Objects by Color
  • Semantics, Grounding, and Truth
• An Application and Some Empirical Results
  • A Simple Application for Color Naming, Pointing Out, and Selecting
    • Outline
    • Constancy
  • Some Empirical Results
• Discussion and Conclusion
• Appendix A: An Architecture for Autonomous Agents
  • Introduction and Overview
  • The GLAIR Architecture
  • Applications
  • Concluding Remarks
  • Acknowledgments
• Appendix B: Derivation of Color Spaces
• Appendix C: Getting the software
• References
• About this document ...