Region-based visual attention analysis with its application in image browsing on small displays

Huiying Liu, Shuqiang Jiang, Qingming Huang, Changsheng Xu, Wen Gao

Abstract: Visual attention has been a hot research point for many years and many new applications are emerging especially for wireless multimedia services. In this paper a novel region-based visual attention is proposed to detect the Regions of Interest (ROI) of images. In the proposed method, density based image segmentation is first performed by regarding region as the perceptive unit, which makes the model robust to the scale of ROIs and contains more perceptive information. To generate region saliency map to detect ROI, global effect and contextual difference are covered in the form of distance factor and adjacency factor respectively. Since different ROIs may have different importance for different purposes, a ROI ranking algorithm is designed for browsing large images on small displays. Experimental results and evaluation reveal that our method works effectively to detect ROIs from images and the users are satisfied with the browsing sequence on small displays.