Video Summarization Using Mpeg-7 Motion Activity and Audio Descriptors

Abstract

We present video summarization and indexing techniques using the MPEG-7 motion activity descriptor. The descriptor can be extracted in the compressed domain and is compact, and hence is easy to extract and match. We establish that the intensity of motion activity of a video shot is a direct indication of its summarizability. We describe video summarization techniques based on sampling in the cumulative motion activity space. We then describe combinations of the motion activity based techniques with generalized sound recognition that enable completely automatic generation of news and sports video summaries. Our summarization is computationally simple and flexible, which allows rapid generation of a summary of any desired length.