Rapid generation of event-based indexes for personalized video digests

Abstract

This paper presents a novel video indexing method for providing timely personalized video delivery services. Several previous research reports have dealt with automatic content-based indexing. However, these systems require a lot of time to manually correct the indexes after preliminary automatic processing, making it difficult to use these indexes in practical services. In our method, reliable content-based indexes can be automatically generated by manually flagging predefined and easily recognizable events while watching the video (without rewinding). The generated indexes use temporal functions of significance based on some parameters predefined for each kind of flagged event. Therefore, we can reduce the time required for flagging and achieve rapid semi-manual video indexing. Finally, we confirm effectiveness of the indexes transformed into a subset of MPEG-7 descriptions in a practical service to automatically construct personalized video digests.