Abstract
We propose a method to predict human saccadic scanpaths on natural images based on a bio-inspired visual attention model. The method integrates three related factors as driven forces to guide eye movements, sequentially-visual saliency, winner-takes-all and visual memory, respectively. When predicting a current fixation of saccadic scanpaths, we follow physiological visual memory characteristics to eliminate the effects of the previous selected fixation. Then, we use winner-takes-all to select the fixation on the current saliency map. Experimental results demonstrate that the proposed model outperform other methods on both static fixation locations and dynamic scanpaths.
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Duan, L., Qiao, H., Wu, C., Yang, Z., Ma, W. (2014). Modeling of Human Saccadic Scanpaths Based on Visual Saliency. In: Pan, JS., Krömer, P., Snášel, V. (eds) Genetic and Evolutionary Computing. Advances in Intelligent Systems and Computing, vol 238. Springer, Cham. https://doi.org/10.1007/978-3-319-01796-9_28
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DOI: https://doi.org/10.1007/978-3-319-01796-9_28
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-01795-2
Online ISBN: 978-3-319-01796-9
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