Digest making method based on turning point analysis

A huge amount of multimedia content is available in the current Web environment. Streaming of video programs has become one of the popular Web-based information services. Automatic digest generation is an important application using video program streams. We have developed a digest making method called PDMS (Personal Digest Making Scheme). PDMS extracts significant scenes and constructs digests automatically using the video program meta data. In PDMS, only a successful play event such as a goal scored was considered significant, and a misplay event, such as a shot that did not score was not taken into account, although such an event may affect the game progress. This paper introduces a new concept of turning point analysis into PDMS. The turning point analysis is based on a winning probability for a sports programs. The winning probability indicates the probability of a home team beating an away team at the end of the game, given the current score and the time elapsed since the beginning of the game. Using the winning probability, we can more precisely evaluate the significance of each event, not merely a successful play but also a misplay. This paper presents turning point analysis for a soccer match. It also gives evaluation results of this extended PDMS, including turning point analysis for a recently broadcasted professional soccer match.