Abstract

To entice the target audience into paying to see the full movie, the production of movie trailers is an integral part of movie industry. Action scene is the main component of a movie trailer. In this paper, we propose an automatic action scene detection algorithm based on the analysis of high-level video structure. The input video is first decomposed into a number of basic components called shots. Then, shots are grouped into semantic-related scenes by taking into account the visual characteristics and temporal dynamics of video. Based on the filmmaking characteristics of action scene, some features of the scene are extracted to feed into the support vector machine for classification. Compared with related works which integrate visual and audio information, our visual based approach is computationally simple yet effective.

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