Mapping semantic script with image processing algorithms to leverage amateur video material in professional production

In this paper, we investigate the issue of amateur production in order to leverage its integration in professional production. We define a conceptual model of the shooting script that represents information about the shooting realization. It enables us to provides the amateur cameraman with prior shooting guidance on an intelligent camcorder. We use image processing algorithms and methods to provide the amateur with real-time shooting feedbacks. After the shooting, these algorithms produce more accurate descriptions that can be compared to the initial prescription. The comparison is guided by satisfaction rules defined by the professional to sort out non conforming sequence. Such rules are also used as query during video shot reviewing. Eventually, we discuss our approach with related works.

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