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Proceedings Paper

Saliency based SIFT keypoints filtration
Author(s): Xin He; Huiyun Jing; Xuefeng Bai; Li Li; Qi Han; Xiamu Niu
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Paper Abstract

In this paper, we propose a novel method to filter the keypoints and reduce redundant keypoints. SIFT (Scale Invariant Feature Transform) is one of the most robust and widely used methods for image matching and object recognition, which is robust to illumination changes, image scaling and rotation. However SIFT generates a large number of redundant keypoints in the background of the scene. Based on saliency detection and salient region selection, the keypoints out of the selected salient region are pruned in our method. The experimental results show that though the repeatability in our method is a little lower than original SIFT (less than 6%), the number of keypoints in our method is significantly reduced (more than 33%).

Paper Details

Date Published: 2 June 2012
PDF: 4 pages
Proc. SPIE 8334, Fourth International Conference on Digital Image Processing (ICDIP 2012), 833415 (2 June 2012);
Show Author Affiliations
Xin He, Harbin Institute of Technology (China)
Huiyun Jing, Harbin Institute of Technology (China)
Xuefeng Bai, Harbin Institute of Technology (China)
Li Li, Harbin Institute of Technology (China)
Qi Han, Harbin Institute of Technology (China)
Xiamu Niu, Harbin Institute of Technology (China)

Published in SPIE Proceedings Vol. 8334:
Fourth International Conference on Digital Image Processing (ICDIP 2012)
Mohamed Othman; Sukumar Senthilkumar; Xie Yi, Editor(s)

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