A Reverse Hierarchy Model for Predicting Eye Fixations

A number of psychological and physiological evidences suggest that early visual attention works in a coarse-to-fine way, which lays a basis for the reverse hierarchy theory (RHT). This theory states that attention propagates from the top level of the visual hierarchy that processes gist and abstract information of input, to the bottom level that processes local details. Inspired by the theory, we develop a computational model for saliency detection in images. First, the original image is downsampled to different scales to constitute a pyramid. Then, saliency on each layer is obtained by image super-resolution reconstruction from the layer above, which is defined as unpredictability from this coarse-to-fine reconstruction. Finally, saliency on each layer of the pyramid is fused into stochastic fixations through a probabilistic model, where attention initiates from the top layer and propagates downward through the pyramid. Extensive experiments on two standard eye-tracking datasets show that the proposed method can achieve competitive results with state-of-the-art models.Comment: CVPR 2014, 27th IEEE Conference on Computer Vision and Pattern Recognition (CVPR). CVPR 201

A Saliency Detection Technique Considering Self- and Mutual-Information

In this paper, we present a novel approach to saliency detection. We define a visually salient region in an image with following two properties; global spatial redundancy, i.e., mutual-information, and local saliency, i.e., self-information or simply the region complexity. The former is its probability of occurrence within the image, whereas the latter defines how much information is contained within a region, and it is quantified by the entropy. By combining the global spatial redundancy measure and local entropy, we can achieve a simple, yet robust saliency detector. We evaluate it quantitatively and qualitatively. The comparison to Itti et al. [6], the spectral residual approach by Hou and Zhang [5], Achanta et al. [13] as well as to Zhai and Shah [14], on publicly available data shows a significant improvement