A Formal Model for Video Shot Segmentation and its Application via Animate Vision

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The first step in a video indexing process is the segmentation of videos into meaningful parts called shots. In this paper we present a formal model of the video shot segmentation process. Starting from a mathematical characterization of the most common transition effects, a video segmentation algorithm capable to detect both abrupt and gradual transitions is proposed. The proposed algorithm is based on the computation of an arbitrary similarity measure between consecutive frames of a video. The algorithm has been tested adopting a similarity metric based on the Animate Vision theory and results have been reported.