Refining a region based attention model using eye tracking data

Zhen Liang, Hong Fu, Zheru Chi, Dagan Feng

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

11 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 languageEnglish
Title of host publication2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings
Pages1105-1108
Number of pages4
DOIs
Publication statusPublished - 1 Dec 2010
Event2010 17th IEEE International Conference on Image Processing, ICIP 2010 - Hong Kong, Hong Kong
Duration: 26 Sep 201029 Sep 2010

Conference

Conference2010 17th IEEE International Conference on Image Processing, ICIP 2010
CountryHong Kong
CityHong Kong
Period26/09/1029/09/10

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

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