Survey of compressed-domain features used in audio-visual indexing and analysis

Hualu Wang, Ajay Divakaran, Anthony Vetro, Shih-Fu Chang, Huifang Sun
<span title="">2003</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kekp3nlexfexzm4yg4msrqoove" style="color: black;">Journal of Visual Communication and Image Representation</a> </i> &nbsp;
In this paper, we attempt to provide a comprehensive and high-level review of audiovisual features that can be extracted from the standard compressed domains, such as MPEG-1 and MPEG-2. The paper is motivated by the myriad of active research works in extraction and application of compressed-domain features in various fields, such as indexing, filtering, and manipulation. Compressed-domain approaches avoid expensive computation and memory requirements involved in decoding and/or re-encoding.
more &raquo; ... cted features are categorized into four groups-spatial visual (e.g., color, texture, edge, shape), motion (e.g., motion field, trajectory), audio (e.g., energy, spectral features, pitch), and coding (e.g., bit rate, frame/block type). For each feature, we briefly discuss the extraction methods, computational complexity, potential effectiveness in applications, and possible limitations caused by compress-domain approaches. Finally, we also discuss the possibilities of extracting some important MPEG-7 visual and audio descriptors directly from the compressed domain.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/s1047-3203(03)00019-1">doi:10.1016/s1047-3203(03)00019-1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/5pueo6wembhafibi3wzqbuk2vi">fatcat:5pueo6wembhafibi3wzqbuk2vi</a> </span>
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