Optimization-Based Automated Home Video

In this paper, we present an optimization-based system that automates home video editing (AVE). This system automatically selects suitable or desirable highlight segments from a set of raw home videos and aligns them with a given piece of incidental music to create an edited video segment to a desired length based on the content of the video and incidental music. We developed an approach for extracting temporal structure and determining the importance of a video segment in order to facilitate the selection of highlight segments. Additionally we extract temporal structure, beats and tempos from the incidental music. In order to create more professional-looking results, the selected highlight segments satisfy a set of editing rules and are matched to the content of the incidental music. This task is formulated as a non-linear 0-1 programming problem and the rules, which are adjustable and increasable, are embedded as constraints. The output video is rendered by connecting the selected highlight video segments with transition effects and the incidental music. Under this framework, we can choose the best-matched music for a given video and support different output styles.