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Contributions au montage automatique de scènes complexes multi-vues en interaction avec l'environnement

Abstract : This thesis, resulting from a collaboration between CRAN and CitizenCam, aims to capture and broadcast public events at a lower cost. Thus, the company wishes to offer an automatic editing system, adaptable to each application context and taking into account the spectators’ requirements. A bibliographical study on the automatic editing of video sequences is presented in the first chapter. This study shows that the existing methods are very specific to the application context and thus not very generalizable. The objective of the second chapter is therefore to propose a methodological approach to automatic editing, based on a generic framework adaptable according to the context, while taking into account user preferences. This approach, based on the knowledge modelling of the application context using the NIAM-ORM method, allows us to identify people (POI) and actions (AOI) of interest. The modelled knowledge also facilitate the choice and configuration of algorithms for extracting the POI and AOI features required for editing. Chapter 3 focuses on implementation of an automatic editing system for municipal councils with the proposal of an original speaker detection method and its identification based on the VLC concept. The broadcasting of basketball matches is covered in Chapter 4 with the proposal of an automatic camera selection method for broadcasting of the AOI "relevant game" with two customizations that are free throw detection and player tracking. Thus, the proposed methodology is validated by its application to this two types of events.
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https://hal.univ-lorraine.fr/tel-02499308
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Florent Lefèvre. Contributions au montage automatique de scènes complexes multi-vues en interaction avec l'environnement. Réseaux et télécommunications [cs.NI]. Université de Lorraine, 2019. Français. ⟨NNT : 2019LORR0239⟩. ⟨tel-02499308v2⟩

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