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Mühling et al. present an audio-visual video concept detection system. Their system extracts visual and auditory bags of words from video data. Visual words are based on SIFT features, auditory words are formed by applying the K-Means algorithm to a Mel-Frequency Cepstral Coefficients analysis of the auditory data. Support vector machines are used for classification.