Object-based Saliency as a Predictor of Attention in Visual Tasks

Michal Dziemianko; Alasdair Clarke; Frank Keller

Object-based Saliency as a Predictor of Attention in Visual Tasks

Michal Dziemianko, Alasdair Clarke, Frank Keller

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

The top-down guidance of visual attention is an important factor allowing humans to effectively process incoming visual information. Our understanding of the processes governing attention is not complete, with growing evidence for attention selection based on cognitive relevance. In this paper, we investigate whether models for salient object detection from computer vision can be used to predict attentional shifts in visual tasks. Our results show that the object-based interpretation of saliency provided by these models is a substantially better
predictor of fixation locations than traditional pixel-based saliency.

Original language	English
Title of host publication	Proceedings for the Annual Meeting of the Cognitive Science Society
Pages	2237-2242
Number of pages	6
Publication status	Published - 2013

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Dziemianko Clarke ET AL 2013 Object-based Saliency as a Predictor of Attention in VisualAccepted author manuscript, 2.61 MB

https://mindmodeling.org/cogsci2013/papers/0409/index.html

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title = "Object-based Saliency as a Predictor of Attention in Visual Tasks",

abstract = "The top-down guidance of visual attention is an important factor allowing humans to effectively process incoming visual information. Our understanding of the processes governing attention is not complete, with growing evidence for attention selection based on cognitive relevance. In this paper, we investigate whether models for salient object detection from computer vision can be used to predict attentional shifts in visual tasks. Our results show that the object-based interpretation of saliency provided by these models is a substantially betterpredictor of fixation locations than traditional pixel-based saliency.",

author = "Michal Dziemianko and Alasdair Clarke and Frank Keller",

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pages = "2237--2242",

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AU - Dziemianko, Michal

AU - Clarke, Alasdair

AU - Keller, Frank

PY - 2013

Y1 - 2013

N2 - The top-down guidance of visual attention is an important factor allowing humans to effectively process incoming visual information. Our understanding of the processes governing attention is not complete, with growing evidence for attention selection based on cognitive relevance. In this paper, we investigate whether models for salient object detection from computer vision can be used to predict attentional shifts in visual tasks. Our results show that the object-based interpretation of saliency provided by these models is a substantially betterpredictor of fixation locations than traditional pixel-based saliency.

AB - The top-down guidance of visual attention is an important factor allowing humans to effectively process incoming visual information. Our understanding of the processes governing attention is not complete, with growing evidence for attention selection based on cognitive relevance. In this paper, we investigate whether models for salient object detection from computer vision can be used to predict attentional shifts in visual tasks. Our results show that the object-based interpretation of saliency provided by these models is a substantially betterpredictor of fixation locations than traditional pixel-based saliency.

M3 - Conference contribution

SP - 2237

EP - 2242

BT - Proceedings for the Annual Meeting of the Cognitive Science Society

ER -

Object-based Saliency as a Predictor of Attention in Visual Tasks

Abstract

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