Does color influence eye movements while exploring videos?

Although visual attention studies consider color as one of the most important features in guiding visual attention, few studies have investigated how color influences eye movements while viewing natural scenes without any particular task. To better understand the visual features that drive attention, the aim of this paper was to quantify the influence of color on eye movements when viewing dynamic natural scenes. The influence of color was investigated by comparing the eye positions of several observers eye-tracked while viewing video stimuli in two conditions: color and grayscale. The comparison was made using the dispersion between the eye positions of observers, the number of attractive regions measured with a clustering method applied to the eye positions, and by comparing eye positions to the predictions of a saliency model. The mean amplitude of saccades and the mean duration of fixations were compared as well. Globally, a slight influence of color on eye movements was measured; only the number of attractive regions for color stimuli was slightly higher than for grayscale stimuli. However, a luminance-based saliency model predicts the eye positions for color stimuli as efficiently as for grayscale stimuli

Contribution of color in saliency model for videos

International audienceMuch research has been concerned with the contribution of the low-level features of a visual scene to the deployment of visual attention. Bottom-up saliency models have been developed to predict the location of gaze according to these features. So far, color besides intensity, contrast and motion is considered as one of the primary features in computing bottom-up saliency. However, its contribution in guiding eye movements when viewing natural scenes has been debated. We investigated the contribution of color information in a bottom-up visual saliency model. The model efficiency was tested using the experimental data obtained on 45 observers who were eye-tracked while freely exploring a large dataset of color and grayscale videos. The two datasets of recorded eye positions, for grayscale and color videos, were compared with a luminance-based saliency model (Marat et al. Int J Comput Vis 82:231–243, 2009). We incorporated chrominance information to the model. Results show that color information improves the performance of the saliency model in predicting eye positions

Contribution of color in saliency model for videos

International audienceMuch research has been concerned with the contribution of the low-level features of a visual scene to the deployment of visual attention. Bottom-up saliency models have been developed to predict the location of gaze according to these features. So far, color besides intensity, contrast and motion is considered as one of the primary features in computing bottom-up saliency. However, its contribution in guiding eye movements when viewing natural scenes has been debated. We investigated the contribution of color information in a bottom-up visual saliency model. The model efficiency was tested using the experimental data obtained on 45 observers who were eye-tracked while freely exploring a large dataset of color and grayscale videos. The two datasets of recorded eye positions, for grayscale and color videos, were compared with a luminance-based saliency model (Marat et al. Int J Comput Vis 82:231–243, 2009). We incorporated chrominance information to the model. Results show that color information improves the performance of the saliency model in predicting eye positions