High Definition Visual Attention based Video Summarization

Abstract

A High Definition visual attention based video summarization algorithm is proposed to extract feature frames and create a video summary. It uses colour histogram shot detection algorithm to separate the video into shots, then applies a novel high definition visual attention algorithm to construct a saliency map for each frame. A multivariate mutual information algorithm is applied to select a feature frame to represent each shot. Finally, those feature frames are processed by a self-organizing map to remove the redundant frames. The algorithm was assessed against manual key frame summaries presented with tested datasets from www.open-video.org. Of the frames selected by the algorithm, 27.8% to 68.1% were in agreement with the manual frame summaries depending on the category and length of the video.