Target detection method based on supervised saliency map and efficient subwindow search

Songtao Liu; Ning Jiang; Zhenxing Liu

doi:10.1117/12.2199215

8 October 2015 Target detection method based on supervised saliency map and efficient subwindow search

Songtao Liu, Ning Jiang, Zhenxing Liu

Proceedings Volume 9675, AOPC 2015: Image Processing and Analysis; 967512 (2015) https://doi.org/10.1117/12.2199215
Event: Applied Optics and Photonics China (AOPC2015), 2015, Beijing, China

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.

Citation Download Citation

Songtao Liu, Ning Jiang, and Zhenxing Liu "Target detection method based on supervised saliency map and efficient subwindow search", Proc. SPIE 9675, AOPC 2015: Image Processing and Analysis, 967512 (8 October 2015); https://doi.org/10.1117/12.2199215

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