Automatic Generation of Summaries for the Web

Many TV broadcasters and film archives are planning to make their collections available on the Web. However, a major problem with large film archives is the fact that it is difficult to search the content visually. A video summary is a sequence of video clips extracted from a longer video. Much shorter than the original, the summary preserves its essential messages. Hence, video summaries may speed up the search significantly. Videos that have full horizontal and vertical resolution will usually not be accepted on the Web, since the bandwidth required to transfer the video is generally very high. If the resolution of a video is reduced in an intelligent way, its content can still be understood. We introduce a new algorithm that reduces the resolution while preserving as much of the semantics as possible. In the MoCA (movie content analysis) project at the University of Mannheim we developed the video summarization component and tested it on a large collection of films. In this paper we discuss the particular challenges which the reduction of the video length poses, and report empirical results from the use of our summarization tool