Audio visual cues for video indexing and retrieval

Authors:
Paisarn Muneesawang;Tahir Amin;Ling Guan
Affiliations:
Dept. of Electrical and Computer Engineering, Naresuan University, Thailand;Dept. of Electrical and Computer Engineering, Ryerson University, Toronto, Canada;Dept. of Electrical and Computer Engineering, Ryerson University, Toronto, Canada
Venue:
PCM'04 Proceedings of the 5th Pacific Rim conference on Advances in Multimedia Information Processing - Volume Part I
Year:
2004

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Abstract

This paper studies content-based video retrieval using the combination of audio and visual features. The visual feature is extracted by an adaptive video indexing technique that places a strong emphasis on accurate characterization of spatio-temporal information within video clips. Audio feature is extracted by a statistical time-frequency analysis method that applies Laplacian mixture models to wavelet coefficients. The proposed joint audio-visual retrieval framework is highly flexible and scalable, and can be effectively applied to various types of video databases.