Human-centered image navigation on mobile devices

How to navigate large images on mobile device is an open problem due to small display screen. Currently region of interest (ROI) image compressing is a popular approach. However, since the semantics of image is diversified by different users, it is hard to extract general ROI. In this paper, we propose a human-centered image navigation method for mobile users with simple human interaction. Different from previous work, we first extract local saliency map (LSM) of an image according to personalized requirement, which can reduce the semantic ambiguity of the image for different users. Based on LSM, we can detect the ROIs of the image, which fully satisfies the different interests of the different users. Experiments and user studies show an encouraging performance of the proposed method.