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Proceedings Paper

Top-down spatiotemporal saliency detection using spectral filtering
Author(s): Wanyi Li; Peng Wang; Hong Qiao
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Paper Abstract

A spectral filtering based method for top-down spatiotemporal saliency detection is proposed. The proposed method enables to favor the salient features of the target object needed to pop out. Here a feature vector representing the salient features of the target object is learned online within the first image in which it is detected or initialized manually. The proper scale of the Gaussian kernel for spectral filtering is selected automatically according to the size ratio of the whole image to the target object. Guided by the top-down information, a top-down, target-related saliency map can be built in subsequent images. This enables to focus on the most relevant salient region and can be extended to complicated computer vision tasks. Experiment results demonstrate the effectiveness of the proposed method.

Paper Details

Date Published: 19 July 2013
PDF: 5 pages
Proc. SPIE 8878, Fifth International Conference on Digital Image Processing (ICDIP 2013), 88782G (19 July 2013); doi: 10.1117/12.2030535
Show Author Affiliations
Wanyi Li, Institute of Automation (China)
Peng Wang, Institute of Automation (China)
Hong Qiao, Institute of Automation (China)


Published in SPIE Proceedings Vol. 8878:
Fifth International Conference on Digital Image Processing (ICDIP 2013)
Yulin Wang; Xie Yi, Editor(s)

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