Edge Detection with Automatic Scale Selection Approach to Improve Coherent Visual Attention Model

An automatic scale selection approach is developed to improve the coherent visual attention model (Le Meur, O., Le Callet, P., Barba, D., Thoreau, D., 2006. A coherent computational approach to model bottom-up visual attention. IEEE Trans. Pattern Anal. Machine Intell. 28 (5), 802-817). The new approach uses linear summation to combine the automatic scale selection attention model with the coherent visual attention model. It is biologically more plausible because two important properties of human vision (i.e. edge detection and scale selection) are used. Its performance is evaluated by a large human fixation dataset. The t-test indicates that the improved model outperforms the original one highly significantly (p<0.01), and thus the new approach furnishes a more accurate model for visual attention prediction.