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Predicting Eye Fixations on Complex Visual Stimuli Using Local Symmetry
KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS. KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
2011 (English)In: Cognitive Computation, ISSN 1866-9956, Vol. 3, no 1, 223-240 p.Article in journal (Refereed) Published
Abstract [en]

Most bottom-up models that predict human eye fixations are based on contrast features. The saliency model of Itti, Koch and Niebur is an example of such contrast-saliency models. Although the model has been successfully compared to human eye fixations, we show that it lacks preciseness in the prediction of fixations on mirror-symmetrical forms. The contrast model gives high response at the borders, whereas human observers consistently look at the symmetrical center of these forms. We propose a saliency model that predicts eye fixations using local mirror symmetry. To test the model, we performed an eye-tracking experiment with participants viewing complex photographic images and compared the data with our symmetry model and the contrast model. The results show that our symmetry model predicts human eye fixations significantly better on a wide variety of images including many that are not selected for their symmetrical content. Moreover, our results show that especially early fixations are on highly symmetrical areas of the images. We conclude that symmetry is a strong predictor of human eye fixations and that it can be used as a predictor of the order of fixation.

Place, publisher, year, edition, pages
2011. Vol. 3, no 1, 223-240 p.
Keyword [en]
Eye movements, Covert visual attention, Local symmetry, Saliency models
National Category
Computer and Information Science
URN: urn:nbn:se:kth:diva-37279DOI: 10.1007/s12559-010-9089-5ISI: 000292777700017ScopusID: 2-s2.0-79952814300OAI: diva2:433034
QC 20110808Available from: 2011-08-08 Created: 2011-08-08 Last updated: 2012-03-20Bibliographically approved

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