The following is a dissertation aimed at understanding what the various
phenomena in visual search teach us about the nature of human visual
representations and processes. I first review some of the major empirical
findings in the study of visual search. I next present a theory of visual
search in terms of what I believe these findings suggest about the
representations and processes underlying ventral visual processing. These
principles are instantiated in a computational model called CASPER (Concurrent
Attention: Serial and Parallel Evaluation with Relations), originally developed
by Hummel, that I have adapted to account for a range of phenomena in visual
search. I then describe an extension of the CASPER model to account for our
ability to search for visual items defined not simply by the features composing
those items but by the spatial relations among those features. Seven
experiments (four main experiments and three replications) are described that
test CASPER's predictions about relational search. Finally, I evaluate the fit
between CASPER's predictions and the empirical findings and show with three
additional simulations that CASPER can account for negative acceleration in
search functions for relational stimuli if one postulates that the visual
system is leveraging an emergent feature that bypasses relational processing.

通过对视觉搜索中的各种现象的研究，本文解析了人类视觉表征和过程的本质，并提出了一种计算模型（CASPER），用于解释视觉搜索中的一系列现象，其中包括关系搜索。通过实验证明 CASPER 模型可以解释关系刺激中搜索功能的负加速度，并揭示视觉系统利用绕过关系处理的新兴特征。