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Compressed domain video saliency detection using global and local spatiotemporal features

Title
Compressed domain video saliency detection using global and local spatiotemporal features
Authors
Lee, Se-HoKang, Je-WonKim, Chang-Su
Ewha Authors
강제원
SCOPUS Author ID
강제원scopus
Issue Date
2016
Journal Title
JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION
ISSN
1047-3203JCR Link1095-9076JCR Link
Citation
vol. 35, pp. 169 - 183
Keywords
Video saliency detectionSpatiotemporal featureCompressed domainVisual attentionPartial decodingImage understandingImage analysisMotion analysis
Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
Indexed
SCIE; SCOPUS WOS scopus
Abstract
A compressed domain video saliency detection algorithm, which employs global and local spatiotemporal (GLST) features, is proposed in this work. We first conduct partial decoding of a compressed video bit-stream to obtain motion vectors and DCT coefficients, from which GLST features are extracted. More specifically, we extract the spatial features of rarity, compactness, and center prior from DC coefficients by investigating the global color distribution in a frame. We also extract the spatial feature of texture contrast from AC coefficients to identify regions, whose local textures are distinct from those of neighboring regions. Moreover, we use the temporal features of motion intensity and motion contrast to detect visually important motions. Then, we generate spatial and temporal saliency maps, respectively, by linearly combining the spatial features and the temporal features. Finally, we fuse the two saliency maps into a spatiotemporal saliency map adaptively by comparing the robustness of the spatial features with that of the temporal features. Experimental results demonstrate that the proposed algorithm provides excellent saliency detection performance, while requiring low complexity and thus performing the detection in real-time. (C) 2015 Elsevier Inc. All rights reserved.
DOI
10.1016/j.jvcir.2015.12.011
Appears in Collections:
엘텍공과대학 > 전자공학과 > Journal papers
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