Adaptation and Annotation of Formula 1 Sport Videos

In this paper, we approach the problem of detecting editing features suitable for video annotation, by paying attention to artifacts and effects introduced in video editing. In particular, a linear transition detection algorithm is presented, which can characterize the transition center and length with high precision. The technique works with sub-frame granularity and is able to include both abrupt cuts and longer dissolves in a single approach. Theoretical justification for the algorithm is provided with an optimization technique for real cases. We present results obtained exploiting the editing features on a Formula 1 video digital library, detecting replays and providing pre classification hints for automatic shot annotation.