Audio visual cues for video indexing and retrieval

Paisarn Muneesawang; Tahir Amin; Ling Guan

doi:10.1007/978-3-540-30541-5_79

Audio visual cues for video indexing and retrieval

Paisarn Muneesawang
, Tahir Amin
, Ling Guan

Naresuan University
Ryerson University

Research output: Contribution to journal › Article › peer-review

2 Citations (Scopus)

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.

Original language	English
Pages (from-to)	642-649
Number of pages	8
Journal	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3331
DOIs	https://doi.org/10.1007/978-3-540-30541-5_79
Publication status	Published - 2004
Externally published	Yes

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10.1007/978-3-540-30541-5_79

Cite this

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JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Audio visual cues for video indexing and retrieval

Abstract

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