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This chapter investigates the foundational theories and abilities underlying human vision, emphasizing their implications for computational vision systems. It begins with an exploration of pivotal theories, including Feature Integration Theory (FIT), Visual Computation Theory (VCT), and Recognition-by-Components Theory (RBC), which collectively illuminate the mechanisms of human perception. The chapter then categorizes human vision into Static Visual Ability (SVA) and Dynamic Visual Ability (DVA), emphasizing their distinct roles: SVA in high-resolution detail recognition and DVA in motion tracking and interaction with dynamic environments. By synthesizing biological insights and computational innovations, this chapter provides a comprehensive framework for integrating principles of human vision into advanced machine vision systems.

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Humans

  • 章节

  • 发表日期：

    2025年

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  • Xin Zhao,
  • Shiyu Hu,
  • Xu-Cheng Yin

摘要

This chapter investigates the foundational theories and abilities underlying human vision, emphasizing their implications for computational vision systems. It begins with an exploration of pivotal theories, including Feature Integration Theory (FIT), Visual Computation Theory (VCT), and Recognition-by-Components Theory (RBC), which collectively illuminate the mechanisms of human perception. The chapter then categorizes human vision into Static Visual Ability (SVA) and Dynamic Visual Ability (DVA), emphasizing their distinct roles: SVA in high-resolution detail recognition and DVA in motion tracking and interaction with dynamic environments. By synthesizing biological insights and computational innovations, this chapter provides a comprehensive framework for integrating principles of human vision into advanced machine vision systems.