| G. Evangelopoulos, A. Zlatintsi, A. Potamianos, P. Maragos, K. Rapantzikos, G. Skoumas, Y. Avrithis |
| Multimodal Saliency and Fusion for Movie Summarization based on Aural, Visual, and Textual Attention |
| IEEE Transactions on Multimedia, 2013. |
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ABSTRACT
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| Multimodal streams of sensory information are naturally parsed and integrated by humans using signal-level feature extraction and higher-level cognitive processes. Detection of attention-invoking audiovisual segments is formulated in this work on the basis of saliency models for the audio, visual and textual information conveyed in a video stream. Aural or auditory 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 orientation. Textual or linguistic saliency is extracted from part-of-speech tagging on the subtitles information available with most movie distributions. The individual saliency streams, obtained from modality-depended cues, are integrated in a multimodal saliency curve, modeling the time-varying perceptual importance of the composite video stream and signifying prevailing sensory events. The multimodal saliency representation forms the basis of a generic, bottom-up video summarization algorithm. Different fusion schemes are evaluated on a movie database of multimodal saliency annotations with comparative results provided across modalities. The produced summaries, based on low-level features and content-independent fusion and selection, are of subjectively high aesthetic and informative quality.
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| 01 January , 2013 |
| G. Evangelopoulos, A. Zlatintsi, A. Potamianos, P. Maragos, K. Rapantzikos, G. Skoumas, Y. Avrithis, "Multimodal Saliency and Fusion for Movie Summarization based on Aural, Visual, and Textual Attention", IEEE Transactions on Multimedia, 2013. |
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