News Video Summarization Based on Spatial and Motion Feature Analysis

摘要

In this paper, an efficient and effective summarization algorithm based on the extraction and analysis of spatial and motion features for MPEG news video is proposed. We focus on video feature analysis techniques based on the compressed domain (i.e., MVs and DCT coefficients), without the need of transformation back to the pixel domain. To give the viewers a quick and enough browse of the news content, we adopted a new strategy that the anchor audio is overlaid with the summarized news video. Hence, the detection of anchor shots and the summarization of news segment subject to a time-budget constraint constitute the two main works in this paper. In summarization of news segments, the Lagrangian multiplier approach was employed to build optimization in allocating time-lengths for all the segmented shots and getting the best perceived motion activity of the summarized video. Experiments show that our summarized news videos present an average MOS score of above 4.0 in a subjective test.