Guiding visual attention by manipulating orientation in images

Visual attention plays an important role in directing our gaze to potentially interesting areas in images. Our attention is involuntarily drawn to areas that are perceptually different from their immediate surroundings. Such areas are labeled “salient.” They originate from variations in principal visual features such as color, intensity, and orientation. In this study, we analyze how manipulating the orientation of a particular region of an image affects human visual attention. Statistical Hough transform is applied on a selected region in an image to construct the edge distribution of that region over a range of orientations. The remainder of the image is analyzed using a weighted statistical Hough transform to obtain the edge distribution in the region's surroundings. We measure the dissimilarity between these two distributions as the region is rotated and show that the region becomes more salient as the dissimilarity is increased. This model also allows us to predict the angle of rotation at which the selected region becomes most salient, which enables us to manipulate the image so that the selected region's saliency is maximized. We apply our method to a set of natural images and verify its effectiveness through eye-tracking.