Video Saliency Incorporating Spatiotemporal Cues and Uncertainty Weighting
We propose a novel algorithm to detect visual saliency from video signals by combining both spatial and temporal information and statistical uncertainty measures. The main novelty of the proposed method is twofold. First, separate spatial and temporal saliency maps are generated, where the computati...
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Published in | IEEE transactions on image processing Vol. 23; no. 9; pp. 3910 - 3921 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
United States
IEEE
01.09.2014
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects | |
Online Access | Get full text |
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Summary: | We propose a novel algorithm to detect visual saliency from video signals by combining both spatial and temporal information and statistical uncertainty measures. The main novelty of the proposed method is twofold. First, separate spatial and temporal saliency maps are generated, where the computation of temporal saliency incorporates a recent psychological study of human visual speed perception. Second, the spatial and temporal saliency maps are merged into one using a spatiotemporally adaptive entropy-based uncertainty weighting approach. The spatial uncertainty weighing incorporates the characteristics of proximity and continuity of spatial saliency, while the temporal uncertainty weighting takes into account the variations of background motion and local contrast. Experimental results show that the proposed spatiotemporal uncertainty weighting algorithm significantly outperforms state-of-the-art video saliency detection models. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 1057-7149 1941-0042 |
DOI: | 10.1109/TIP.2014.2336549 |