A human visual model-based approach of the visual attention and performance evaluation

Olivier Le Meur; Dominique Barba; Patrick Le Callet; Dominique Thoreau

doi:10.1117/12.596188

18 March 2005 A human visual model-based approach of the visual attention and performance evaluation

Olivier Le Meur, Dominique Barba, Patrick Le Callet, Dominique Thoreau

Proceedings Volume 5666, Human Vision and Electronic Imaging X; (2005) https://doi.org/10.1117/12.596188
Event: Electronic Imaging 2005, 2005, San Jose, California, United States

Abstract

In this paper, a coherent computational model of visual selective attention for color pictures is described and its performances are precisely evaluated. The model based on some important behaviours of the human visual system is composed of four parts: visibility, perception, perceptual grouping and saliency map construction. This paper focuses mainly on its performances assessment by achieving extended subjective and objective comparisons with real fixation points captured by an eye-tracking system used by the observers in a task-free viewing mode. From the knowledge of the ground truth, qualitatively and quantitatively comparisons have been made in terms of the measurement of the linear correlation coefficient (CC) and of the Kulback Liebler divergence (KL). On a set of 10 natural color images, the results show that the linear correlation coefficient and the Kullback Leibler divergence are of about 0.71 and 0.46, respectively. CC and Kl measures with this model are respectively improved by about 4% and 7% compared to the best model proposed by L.Itti. Moreover, by comparing the ability of our model to predict eye movements produced by an average observer, we can conclude that our model succeeds quite well in predicting the spatial locations of the most important areas of the image content.

Citation Download Citation

Olivier Le Meur, Dominique Barba, Patrick Le Callet, and Dominique Thoreau "A human visual model-based approach of the visual attention and performance evaluation", Proc. SPIE 5666, Human Vision and Electronic Imaging X, (18 March 2005); https://doi.org/10.1117/12.596188

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