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

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Abstract

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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Notes

  1. See http://ireport.cnn.com/.

  2. MediaMap is a Celtic project which aims at innovating in the area of audiovisual content production, in particular in the niche of UGC. See http://www.mediamapproject.org/ for further details. The content of this paper is the sole responsibility of the authors and in no way represents the view of the Celtic-Initiative.

  3. VITEC Multimedia is a leader in digital video technology and is developing and manufacturing original multimedia products at the point where micro-computing and video technology meet. See http://www.VITECmm.com.

  4. SkemA is specialized in the development of Web and Mobile video platforms. They provide UGC-oriented guidance solutions to leverage content quality and ensures its relevance according to predefined editorial guidelines. See http://www.skema.fr/.

  5. See http://protege.stanford.edu/.

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Authors and Affiliations

  1. Centre de Recherches de Royallieu, Université de Technologie de Compiègne, HeuDiaSyC JRU 6599, BP 20529 60205, Compiègne Cedex, France

    Benjamin Diemert, Ana Pinzari, Claude Moulin, Marie-Hélène Abel & Marcus M. Shawky

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  1. Benjamin Diemert
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  2. Ana Pinzari
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  3. Claude Moulin
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  4. Marie-Hélène Abel
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  5. Marcus M. Shawky
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Correspondence to Benjamin Diemert.

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Diemert, B., Pinzari, A., Moulin, C. et al. Mapping semantic script with image processing algorithms to leverage amateur video material in professional production. Multimed Tools Appl 62, 333–358 (2013). https://doi.org/10.1007/s11042-011-0908-9

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