Detecting video saliency via local motion estimation

In the last decades, saliency detection was extensively studied. The number of computational models that help to detect salient regions in still images is increasing, whereas, detecting salient regions in videos is in its early stages. In this paper we propose a video saliency detection method using local motion estimation. Starting from a patch, the problem of saliency detection is modeled as a growing region starting from a region which contains the higher motion information to the background. Local saliency is measured by combining local motion estimation and local surrounding contrast which leads to the construction of foreground and background patches. Experiments have proved that The proposed method outperforms state-of-the-art methods over two benchmark datasets.