JITTER-ROBUST VIDEO RETARGETING WITH KALMAN FILTER AND ATTENTION SALIENCY FUSION NETWORK

In this paper, we propose a novel framework for video retargeting with Kalman filter and Attention Saliency Fusion Network (ASFN). First, we estimate the importance map which account for content-aware saliency map. Aspect ratio of video is then resized by adaptive scaling function. Finally, Kalman filter is applied to the image sequence for alleviating jittering and wavy effect of moving objects. Proposed method uses two consequence images which can be implemented on real-time application. Experimental results validate the proposed framework can achieve content-preserving results while alleviating the jitter effect.