Clarification of Video Retrieval Query Results by the Automated Insertion of Supporting Shots
This work addresses the need for more general-purpose automated video editing tools, though it appears incremental as it builds on existing annotation and segmentation systems.
The paper tackles the problem of domain-specific limitations in computational video editing systems by developing a generic editing strategy based on cinema narrative principles, demonstrating its flexibility through examples in an automated system.
Computational Video Editing Systems output video generally follows a particular form, e.g. conversation or music videos, in this way they are domain specific. We describe a recent development in our video annotation and segmentation system to support general computational video editing in which we derive a single generic editing strategy from general cinema narrative principles instead of using a hierarchical film gram-mar. We demonstrate how this single principle coupled with a database of scripts derived from annotated videos leverages the existing video editing knowledge encoded within the editing of those sequences in a flexible and generic manner. We discuss the cinema theory foundations for this generic editing strategy, review the algorithms used to effect it, and goon by means of examples to show its appropriateness in an automated system.