Video partitioning and camera motion characterization for content-based video indexing

This paper describes an original approach which jointly addresses the two issues of video partitioning and camera motion characterization in the context of content-based video indexing. It can cope with scenes containing moving objects. Detection of shot changes and recognition of the movements of the system-of-view are both derived from the computation, at each time instant, of the dominant motion in the image represented by a 2D affine model, and from the variation of the size of its associated support. The successive steps of the method rely on statistical techniques ensuring robustness and efficiency. Results on a real documentary video are reported and validate the proposed approach