4 research outputs found
Gaze Distribution Analysis and Saliency Prediction Across Age Groups
Knowledge of the human visual system helps to develop better computational
models of visual attention. State-of-the-art models have been developed to
mimic the visual attention system of young adults that, however, largely ignore
the variations that occur with age. In this paper, we investigated how visual
scene processing changes with age and we propose an age-adapted framework that
helps to develop a computational model that can predict saliency across
different age groups. Our analysis uncovers how the explorativeness of an
observer varies with age, how well saliency maps of an age group agree with
fixation points of observers from the same or different age groups, and how age
influences the center bias. We analyzed the eye movement behavior of 82
observers belonging to four age groups while they explored visual scenes.
Explorativeness was quantified in terms of the entropy of a saliency map, and
area under the curve (AUC) metrics was used to quantify the agreement analysis
and the center bias. These results were used to develop age adapted saliency
models. Our results suggest that the proposed age-adapted saliency model
outperforms existing saliency models in predicting the regions of interest
across age groups
The framework of our proposed study.
<p>It consist of two parts, analysis part and proposed age-adapted saliency model as shown in figure, 29 years is mean age of adult observers. The sample image 1 is same for both of the models and it is only representation of the original image.</p
Gaze distribution analysis and saliency prediction across age groups.
International audienceKnowledge of the human visual system helps to develop better computational models of visual attention. State-of-the-art models have been developed to mimic the visual attention system of young adults that, however, largely ignore the variations that occur with age. In this paper, we investigated how visual scene processing changes with age and we propose an age-adapted framework that helps to develop a computational model that can predict saliency across different age groups. Our analysis uncovers how the explorativeness of an observer varies with age, how well saliency maps of an age group agree with fixation points of observers from the same or different age groups, and how age influences the center bias tendency. We analyzed the eye movement behavior of 82 observers belonging to four age groups while they explored visual scenes. Explorative-ness was quantified in terms of the entropy of a saliency map, and area under the curve (AUC) metrics was used to quantify the agreement analysis and the center bias tendency. Analysis results were used to develop age adapted saliency models. Our results suggest that the proposed age-adapted saliency model outperforms existing saliency models in predicting the regions of interest across age groups