Video summarization using motion descriptors

We describe a technique for video summarization that uses motion descriptors computed in the compressed domain to speed up conventional color based video summarization technique. The basic hypothesis of the work is that the intensity of motion activity of a video segment is a direct indication of its “summarizability.” We present experimental verification of this hypothesis. We are thus able to quickly identify easy to summarize segments of a video sequence since they have a low intensity of motion activity. Moreover, the compressed domain extraction of motion activity intensity is much simpler than the color-based calculations. We are able to easily summarize these segments by simply choosing a key-frame at random from each low-activity segment. We can then apply conventional color-based summarization techniques to the remaining segments. We are thus able to speed up color-based summarization techniques by reducing the number of segments on which computationally more expensive color-based computation is needed.