Video summarization based on key-places clustering and logical story units

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Video content can be accessed by retrieval or browsing. Retrieval is useful when the user know exactly what he/she is looking for. Browsing is useful when the user only needs an overview of the content. In a sense, retrieval is like looking for something from the index of a book while browsing is from the table of content (ToC). Video summarization is the process of generating an audio-visual ToC to help quickly capture the content of a video. The proposed research program targets video summarization. The objective is to develop and integrate multimodal analysis tools to segment a video into logical story units (LSU) based on a new automatic key-places clustering. This will be integrated into a LSU-based GUI, rather than a standard shot- or key-frame-based one, that provides a graphical ToC to the user with the possibility to access parts of the video from it. The GUI should be adaptable to allow user to access video based on his preferences and compatible with the TRECVID evlauation. Video indexing is a very active research topic. Many researches are still needed to reduce the so-called "semantic gap" between low-level features and human understanding. This project wants to be a contribution to this important field but through the video summarization "lense". In particular, a LSU-based videosummarization GUI will be an original contribution of the research program for the advancement of knowledge in the field of visual content usability and for the information technology sector.