Model-based approach to study of mechanisms of complex image viewing

L. N. Podladchikova, D. G. Shaposhnikov, A. V. Tikidgji-Hamburyan, Tatiana Koltunova, R. A. Tikidgji-Hamburyan, Valentina I. Gusakova, Alexander V. Golovan

Optical Memory and Neural Networks · 2009 · 12 citations · 11 references

Abstract

A model-based approach to study complex image viewing mechanisms and the first results of its implementation are presented. The choice of the most informative regions (MIRs) is performed according to results of psychophysical tests with high-accuracy tracking of eye movements. For three test images, the MIRs were determined as image regions with maximal density of gaze fixations for the all subjects (n = 9). Individual image viewing scanpaths (n= 49) were classified into three basic types (i.e. “viewing”, “object-consequent”, and “object-returned” scanpaths). Task-related and temporal dynamics of eye movement parameters for the same subjects have been found. Artificial image scanpaths similar to experimental have been obtained by means of gaze attraction function.

References

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