Predicting Eye Fixations Using Computer Vision Techniques

The goal of this work is to study mechanisms of visual attention to assist visual perception for patients suffering from age-related macular degeneration (AMD) or retinitis pigmentosa (RP) through artificial retina devices. We present a method to predict where humans look; we extend a visual saliency model by incorporating additional features and use this model to obtain saliency maps. These are thresholded at different scales to estimate the points of an image upon which the human eye fixates as well as the exact sequence of these fixations. The sequence of fixations extracted is further used to identify the part of the image that will mostly attract visual attention. Contrary to most existing approaches our method can indicate specific coordinates for the fixation points rather than generic areas that may attract visual attention and is thus more appropriate to imitate human fixations. Our method performs marginally better than the well-known method for saliency prediction we compare against (≈76% accuracy) and very satisfactorily in terms of estimating the sequence of fixations upon any given image (up to 98% accuracy).