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Audio-visual content analysis in P2P: the SAPIR approach

Walter Allasia, Fabrizio Falchi, Francesco Gallo, Mouna Kacimi, Aaron Kaplan, Jonathan Mamou, Yosi Mass, Nicola Orio
Content based search in audio-visual collections requires media specific analysis for extracting low level features to be efficiently indexed and searched. We present the SAPIR media framework for analyzing digital content and representing the extracted features in a common schema. The framework contains splitters of compound objects to simple objects to deal with complex media like videos, using image and speech analyzers. The extracted features are then merged into a common representation. We report usage of this framework in the SAPIR demo.
1st Workshop on Automated Information Extraction in Media Production AIEMPro, Turin, Italy, Sept 1-5, 2008