Parallel processing of efficient, heterogeneous visual search with real-world objects

Wang, Zhiyuan

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https://hdl.handle.net/2142/92989 Copy

Description

Title

Parallel processing of efficient, heterogeneous visual search with real-world objects

Author(s)

Wang, Zhiyuan

Issue Date

2016-05-12

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

Lleras, Alejandro

Department of Study

Psychology

Discipline

Psychology

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.A.

Degree Level

Thesis

Keyword(s)

• visual search
• parallel processing
• heterogeneity
• logarithmic

Abstract

Previous work in our lab has demonstrated that efficient visual search has a reaction time by set size function that is best characterized by logarithmic curves, and the steepness of these logarithmic curves is determined by the similarity between target and distractor items (Buetti et al., in press). This thesis presents a theoretical account of these phenomena, emphasizing that a parallel, unlimited capacity, exhaustive processing system must be underlying such data. Two experiments were conducted to expand our findings to a set of real-world stimuli, in both homogeneous and heterogeneous search displays. Based on our current theory and numerical simulations, we were able to very accurately predict RT performance in heterogeneous search using parameters from homogeneous search tasks of a different group of subjects. By examining the systematic deviation of our predictions from observed data, we concluded that early visual processing for individual items were not independent. Instead, items in homogeneous displays seemed to facilitate each other's processing by a multiplicative factor. These results challenge previous accounts of heterogeneity effects in visual search, and demonstrate the explanatory and predictive power of our current theory of visual search.

Graduation Semester

2016-08

Type of Resource

text

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http://hdl.handle.net/2142/92989

Copyright and License Information

Copyright 2016 Zhiyuan Wang

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