Target-distractor distinctiveness guides efficient search

Xu, Zoe Jing

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https://hdl.handle.net/2142/124501 Copy

Description

Title

Target-distractor distinctiveness guides efficient search

Author(s)

Xu, Zoe Jing

Issue Date

2024-04-10

Director of Research (if dissertation) or Advisor (if thesis)

• Lleras, Alejandro
• Buetti, Simona

Doctoral Committee Chair(s)

• Lleras, Alejandro
• Buetti, Simona

Committee Member(s)

• Beck, Diane
• Christianson, Kiel
• Xia, Yan

Department of Study

Psychology

Discipline

Psychology

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• Visual Search
• Feature Dimension Combination

Language

eng

Abstract

Visual search is a common activity that people engage in regularly. Efficient search, where the target is distinct from distractors, is typically easy to perform. It is believed that efficient search primarily relies on a stage of parallel processing where all the locations in the scene are examined simultaneously to determine the target’s location. However, the specific type of parallel processing and its guidance on efficient search are still subjects of debate. The Target Contrast Signal Theory proposes that during parallel search, a comparison is made between the target template and display items, with distinctiveness signals being accumulated for each item. These distinctiveness signals then guide the search, determining whether an item should be rejected as a distractor, or should be attended to as a potential target. In this thesis, I use computational modeling to investigate the nature of comparisons made during parallel processing and the composition of distinctiveness signals when comparisons are made on multiple feature dimensions. Chapter 2 explores the nature of the parallel comparisons that provide distinctiveness signals in efficient search. Chapter 3 investigates how distinctiveness along shape and texture dimensions combines to guide bidimensional search. Chapter 4 delves into how distinctiveness along color, shape, and texture dimensions combine to guide tridimensional search. The studies conducted in this thesis offer a better understanding of the attentional guidance mechanisms involved in efficient visual search, and also provide a mathematical modeling framework to predict complex search performance based on simpler search performance.

Graduation Semester

2024-05

Type of Resource

Text

Handle URL

https://hdl.handle.net/2142/124501

Copyright and License Information

Copyright 2024 Zoe Jing Xu

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