Personal Video Manager: Managing and Mining Home Video Collections

Home video collections constitute an important source of content to be experienced within the digital entertainment context. To make such content easy to access and reuse, various video analysis technologies have been researched and developed to extract video assets for management tasks, including video shot/scene detection, keyframe extraction, and video skimming/summarization. However, one less addressed issue is to investigate how useful those assets are in helping consumers managing their video collections and the usage pattern of the assets. In this paper, we present Personal Video Manager, both as a home video management system and an explorative research platform to enable a systematic analysis and understanding of consumers’ demand on video assets and video processing technologies. For understanding consumer’s interest, PVM adopts database management technologies to model and archive how consumers identify video assets and utilize them for management tasks. The PVM mining engine performs data mining on such archived data to mine useful knowledge of consumer’s preference on video assets and behavior on utilizing the assets. As revealed in the experiment, consumer's interaction embeds rich information to be leveraged in developing more effective video analysis technologies.