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Proceedings Paper

Target detection method based on supervised saliency map and efficient subwindow search
Author(s): Songtao Liu; Ning Jiang; Zhenxing Liu
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Paper Abstract

In order to realize fast target detection under complex image scene, a novel method is proposed based on supervised saliency map and efficient subwindow search. Supervised saliency map generation mainly includes: (1) the original image is segmented by different parameters to obtain multi-segmentation results; (2) regional feature is mapped for salient value by random forest regressor; (3) obtain saliency map by fusing multi-level segmentation results. Efficient subwindow search method is implemented by transforming salient target detection as maximum saliency density, and using branch and bound algorithm to localize the maximum saliency density in global optimum. The experimental results show that the new method can not only detect salient region, but also recognize this region in some extent.

Paper Details

Date Published: 8 October 2015
PDF: 7 pages
Proc. SPIE 9675, AOPC 2015: Image Processing and Analysis, 967512 (8 October 2015); doi: 10.1117/12.2199215
Show Author Affiliations
Songtao Liu, Dalian Naval Academy (China)
Ning Jiang, Dalian Naval Academy (China)
Zhenxing Liu, Dalian Naval Academy (China)

Published in SPIE Proceedings Vol. 9675:
AOPC 2015: Image Processing and Analysis
Chunhua Shen; Weiping Yang; Honghai Liu, Editor(s)

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