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 mod...
The problem of predicting where people look at, or equivalently salient region detection, has been r...
Automatically predicting human eye fixations is a useful technique that can facilitate many multimed...
Understanding where people look in images is an important problem in computer vision. Despite signif...
Most bottom-up models that predict human eye fixations are based on contrast features. The saliency ...
Humans are very sensitive to symmetry in visual patterns. Reaction time experiments show that symmet...
Humans are very sensitive to symmetry in visual patterns. Reaction time experiments show that symmet...
Humans are very sensitive to symmetry in visual patterns. Symmetry is detected and recognized very r...
Humans are very sensitive to symmetry in visual patterns. Symmetry is detected and recognized very r...
By predicting where humans look in natural scenes, we can understand how they perceive complex natur...
Our eyes make several movements per second. When, for example, reading this line of text, our eyes c...
International audienceHumans are highly sensitive to symmetry. During scene exploration, the area of...
AbstractEye tracking has become the de facto standard measure of visual attention in tasks that rang...
Current computational models of visual salience accurately predict the distribution of fixations on ...
Under natural viewing conditions, human observers shift their gaze to allocate processing resources ...
Springer New York. ISSN : 1866-9956International audienceWhen looking at a scene, we frequently move...
The problem of predicting where people look at, or equivalently salient region detection, has been r...
Automatically predicting human eye fixations is a useful technique that can facilitate many multimed...
Understanding where people look in images is an important problem in computer vision. Despite signif...
Most bottom-up models that predict human eye fixations are based on contrast features. The saliency ...
Humans are very sensitive to symmetry in visual patterns. Reaction time experiments show that symmet...
Humans are very sensitive to symmetry in visual patterns. Reaction time experiments show that symmet...
Humans are very sensitive to symmetry in visual patterns. Symmetry is detected and recognized very r...
Humans are very sensitive to symmetry in visual patterns. Symmetry is detected and recognized very r...
By predicting where humans look in natural scenes, we can understand how they perceive complex natur...
Our eyes make several movements per second. When, for example, reading this line of text, our eyes c...
International audienceHumans are highly sensitive to symmetry. During scene exploration, the area of...
AbstractEye tracking has become the de facto standard measure of visual attention in tasks that rang...
Current computational models of visual salience accurately predict the distribution of fixations on ...
Under natural viewing conditions, human observers shift their gaze to allocate processing resources ...
Springer New York. ISSN : 1866-9956International audienceWhen looking at a scene, we frequently move...
The problem of predicting where people look at, or equivalently salient region detection, has been r...
Automatically predicting human eye fixations is a useful technique that can facilitate many multimed...
Understanding where people look in images is an important problem in computer vision. Despite signif...