Just-in-time personalized video presentations

Using high-quality video cameras on mobile devices, it is relatively easy to capture a significant volume of video content for community events such as local concerts or sporting events. A more difficult problem is selecting and sequencing individual media fragments that meet the personal interests of a viewer of such content. In this paper, we consider an infrastructure that supports the just-in-time delivery of personalized content. Based on user profiles and interests, tailored video mash-ups can be created at view-time and then further tailored to user interests via simple end-user interaction. Unlike other mash-up research, our system focuses on client-side compilation based on personal (rather than aggregate) interests. This paper concentrates on a discussion of language and infrastructure issues required to support just-in-time video composition and delivery. Using a high school concert as an example, we provide a set of requirements for dynamic content delivery. We then provide an architecture and infrastructure that meets these requirements. We conclude with a technical and user analysis of the just-in-time personalized video approach.