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Detection of perceptually important video events is formulated here on the basis of saliency models for the audio, visual and textual information conveyed in a video stream. Audio saliency is assessed by cues that quantify multifrequency waveform modulations, extracted through nonlinear operators and energy tracking. Visual saliency is measured through a spatiotemporal attention model driven by intensity, color and motion. Text saliency is extracted from part-of-speech tagging on the subtitlesdoi:10.1109/icassp.2009.4960393 dblp:conf/icassp/EvangelopoulosZSRPMA09 fatcat:hvqgfwvuc5d3pndvvsjbctaknq