Literature DB >> 22711998

TAM: Explaining off-object fixations and central fixation tendencies as effects of population averaging during search.

Gregory J Zelinsky1.   

Abstract

Understanding how patterns are selected for both recognition and action, in the form of an eye movement, is essential to understanding the mechanisms of visual search. It is argued that selecting a pattern for fixation is time consuming-requiring the pruning of a population of possible saccade vectors to isolate the specific movement to the potential target. To support this position, two experiments are reported showing evidence for off-object fixations, where fixations land between objects rather than directly on objects, and central fixations, where initial saccades land near the center of scenes. Both behaviors were modeled successfully using TAM (Target Acquisition Model; Zelinsky, 2008). TAM interprets these behaviors as expressions of population averaging occurring at different times during saccade target selection. A large population early during search results in the averaging of the entire scene and a central fixation; a smaller population later during search results in averaging between groups of objects and off-object fixations.

Entities:  

Year:  2012        PMID: 22711998      PMCID: PMC3375685          DOI: 10.1080/13506285.2012.666577

Source DB:  PubMed          Journal:  Vis cogn        ISSN: 1350-6285


  73 in total

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Authors:  J T McIlwain
Journal:  J Neurophysiol       Date:  1975-03       Impact factor: 2.714

2.  Visual search: the role of peripheral information measured using gaze-contingent displays.

Authors:  Wilson S Geisler; Jeffrey S Perry; Jiri Najemnik
Journal:  J Vis       Date:  2006-08-03       Impact factor: 2.240

3.  Saccade target selection: Do distractors affect saccade accuracy?

Authors:  John M Findlay; Hazel I Blythe
Journal:  Vision Res       Date:  2008-08-22       Impact factor: 1.886

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Authors:  B C Motter; E J Belky
Journal:  Vision Res       Date:  1998-06       Impact factor: 1.886

5.  The Slow Time-Course of Visual Attention

Authors: 
Journal:  Cogn Psychol       Date:  1996-02       Impact factor: 3.468

6.  Using eye saccades to assess the selectivity of search movements.

Authors:  G J Zelinsky
Journal:  Vision Res       Date:  1996-07       Impact factor: 1.886

7.  Population coding of saccadic eye movements by neurons in the superior colliculus.

Authors:  C Lee; W H Rohrer; D L Sparks
Journal:  Nature       Date:  1988-03-24       Impact factor: 49.962

8.  The role of visual attention in saccadic eye movements.

Authors:  J E Hoffman; B Subramaniam
Journal:  Percept Psychophys       Date:  1995-08

9.  Shifts in selective visual attention: towards the underlying neural circuitry.

Authors:  C Koch; S Ullman
Journal:  Hum Neurobiol       Date:  1985

10.  The zoom lens of attention: Simulating shuffled versus normal text reading using the SWIFT model.

Authors:  Daniel J Schad; Ralf Engbert
Journal:  Vis cogn       Date:  2012-05-23
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  10 in total

1.  Modeling guidance and recognition in categorical search: bridging human and computer object detection.

Authors:  Gregory J Zelinsky; Yifan Peng; Alexander C Berg; Dimitris Samaras
Journal:  J Vis       Date:  2013-10-08       Impact factor: 2.240

2.  Modelling eye movements in a categorical search task.

Authors:  Gregory J Zelinsky; Hossein Adeli; Yifan Peng; Dimitris Samaras
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2013-09-09       Impact factor: 6.237

Review 3.  The what, where, and why of priority maps and their interactions with visual working memory.

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Journal:  Ann N Y Acad Sci       Date:  2015-01-07       Impact factor: 5.691

4.  Eye movement prediction and variability on natural video data sets.

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Journal:  Vis cogn       Date:  2012-03-26

Review 5.  Using multidimensional scaling to quantify similarity in visual search and beyond.

Authors:  Michael C Hout; Hayward J Godwin; Gemma Fitzsimmons; Arryn Robbins; Tamaryn Menneer; Stephen D Goldinger
Journal:  Atten Percept Psychophys       Date:  2016-01       Impact factor: 2.199

6.  The utility of modeling word identification from visual input within models of eye movements in reading.

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Journal:  Vis cogn       Date:  2012-05-23

7.  Medium versus difficult visual search: How a quantitative change in the functional visual field leads to a qualitative difference in performance.

Authors:  Johan Hulleman; Kristofer Lund; Paul A Skarratt
Journal:  Atten Percept Psychophys       Date:  2020-01       Impact factor: 2.199

8.  Centre-of-Gravity Fixations in Visual Search: When Looking at Nothing Helps to Find Something.

Authors:  Dustin Venini; Roger W Remington; Gernot Horstmann; Stefanie I Becker
Journal:  J Ophthalmol       Date:  2014-06-03       Impact factor: 1.909

9.  Temporal Limitations of the Standard Leaky Integrate and Fire Model.

Authors:  Liya Merzon; Tatiana Malevich; Georgiy Zhulikov; Sofia Krasovskaya; W Joseph MacInnes
Journal:  Brain Sci       Date:  2019-12-27

10.  Weighting the factors affecting attention guidance during free viewing and visual search: The unexpected role of object recognition uncertainty.

Authors:  Souradeep Chakraborty; Dimitris Samaras; Gregory J Zelinsky
Journal:  J Vis       Date:  2022-03-02       Impact factor: 2.004

  10 in total

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