Learning Video Saliency from Human Gaze Using Candidate Selection

Abstract

During recent years remarkable progress has been made in visual saliency modeling. Our interest is in video saliency. Since videos are fundamentally different from still images, they are viewed differently by human observers. For example, the time each video frame is observed is a fraction of a second, while a still image can be viewed leisurely. Therefore… (More)
DOI: 10.1109/CVPR.2013.152
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