Abstract
The objective of the work reported here is to provide an automatic, context-of-capture categorization, structure detection and segmentation of news broadcasts employing a multimodal semantic based approach. We assume that news broadcasts can be described with context-free grammars that specify their structural characteristics. We propose a system consisting of two main types of interoperating units: The recognizer unit consisting of several modules and a parser unit. The recognizer modules (audio, video and semantic recognizer) analyze the telecast and each one identifies hypothesized instances of features in the audiovisual input. A probabilistic parser analyzes the identifications provided by the recognizers. The grammar represents the possible structures a news telecast may have, so the parser can identify the exact structure of the analyzed telecast.
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Jacobs, A., Ioannidis, G.T., Christodoulakis, S., Moumoutzis, N., Georgoulakis, S., Papachristoudis, Y. (2007). Automatic, Context-of-Capture-Based Categorization, Structure Detection and Segmentation of News Telecasts. In: Thanos, C., Borri, F., Candela, L. (eds) Digital Libraries: Research and Development. DELOS 2007. Lecture Notes in Computer Science, vol 4877. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77088-6_27
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DOI: https://doi.org/10.1007/978-3-540-77088-6_27
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