Wei Jiang, Courtenay Cotton, Shih-Fu Chang, Dan Ellis, Alexander C. Loui. Audio-Visual Atoms for Generic Video Concept Classification. ACM Transactions on Multimedia Computing, Communications and Applications, 6(3):1-19, 2010.
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We investigate the challenging issue of joint audio-visual analysis of generic videos targeting at concept detection. We extract a novel local representation, Audio-Visual Atom (AVA), which is defined as a region track associated with regional visual features and audio onset features. We develop a hierarchical algorithm to extract visual atoms from generic videos, and locate energy onsets from the corresponding soundtrack by time-frequency analysis. Audio atoms are extracted around energy onsets. Visual and audio atoms form AVAs, based on which discriminative audio-visual codebooks are constructed for concept detection. Experiments over Kodak's consumer benchmark videos confirm the effectiveness of our approach
@article{Jiang:Tomccap2010,
Author = {Jiang, Wei and Cotton, Courtenay and Chang, Shih-Fu and Ellis, Dan and C. Loui, Alexander},
Title = {Audio-Visual Atoms for Generic Video Concept Classification},
Journal = {ACM Transactions on Multimedia Computing, Communications and Applications},
Volume = {6},
Number = {3},
Pages = {1--19},
Publisher = {ACM},
Address = {New York, NY, USA},
Year = {2010}
}
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