Refining a region based attention model using eye tracking data

Zhen Liang; Hong Fu; Zheru Chi; Dagan Feng

doi:10.1109/ICIP.2010.5651804

Refining a region based attention model using eye tracking data

Zhen Liang, Hong Fu, Zheru Chi, Dagan Feng

The Hong Kong Polytechnic University

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

12 Citations (Scopus)

Abstract

Computational visual attention modeling is a topic of increasing importance in machine understanding of images. In this paper, we present an approach to refine a region based attention model with eye tracking data. This paper has three main contributions. (1) A concept of fixation mask is proposed to describe the region saliency of an image by weighting the segmented regions using importance measures obtained in the Human Visual System (HVS) or computational models. (2) A Genetic Algorithm (GA) scheme for refining a region based attention model is proposed. (3) An evaluation method is developed to measure the correlation between the result from the computational model and that from the HVS in terms of fixation mask.

Original language	English
Title of host publication	2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings
Pages	1105-1108
Number of pages	4
DOIs	https://doi.org/10.1109/ICIP.2010.5651804
Publication status	Published - 1 Dec 2010
Event	2010 17th IEEE International Conference on Image Processing, ICIP 2010 - Hong Kong, Hong Kong Duration: 26 Sept 2010 → 29 Sept 2010

Conference

Conference	2010 17th IEEE International Conference on Image Processing, ICIP 2010
Country/Territory	Hong Kong
City	Hong Kong
Period	26/09/10 → 29/09/10

Keywords

Eye tracking data
Fixation mask
Genetic algorithm
Regions of interest
Visual attention model

ASJC Scopus subject areas

Software
Computer Vision and Pattern Recognition
Signal Processing

More information

10.1109/ICIP.2010.5651804

Cite this

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abstract = "Computational visual attention modeling is a topic of increasing importance in machine understanding of images. In this paper, we present an approach to refine a region based attention model with eye tracking data. This paper has three main contributions. (1) A concept of fixation mask is proposed to describe the region saliency of an image by weighting the segmented regions using importance measures obtained in the Human Visual System (HVS) or computational models. (2) A Genetic Algorithm (GA) scheme for refining a region based attention model is proposed. (3) An evaluation method is developed to measure the correlation between the result from the computational model and that from the HVS in terms of fixation mask.",

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AB - Computational visual attention modeling is a topic of increasing importance in machine understanding of images. In this paper, we present an approach to refine a region based attention model with eye tracking data. This paper has three main contributions. (1) A concept of fixation mask is proposed to describe the region saliency of an image by weighting the segmented regions using importance measures obtained in the Human Visual System (HVS) or computational models. (2) A Genetic Algorithm (GA) scheme for refining a region based attention model is proposed. (3) An evaluation method is developed to measure the correlation between the result from the computational model and that from the HVS in terms of fixation mask.

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KW - Fixation mask

KW - Genetic algorithm

KW - Regions of interest

KW - Visual attention model

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M3 - Conference article published in proceeding or book

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BT - 2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings

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ER -

Refining a region based attention model using eye tracking data

Abstract

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Keywords

ASJC Scopus subject areas

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