Paper
2 June 2012 Saliency based SIFT keypoints filtration
Xin He, Huiyun Jing, Xuefeng Bai, Li Li, Qi Han, Xiamu Niu
Author Affiliations +
Proceedings Volume 8334, Fourth International Conference on Digital Image Processing (ICDIP 2012); 833415 (2012) https://doi.org/10.1117/12.946105
Event: Fourth International Conference on Digital Image Processing (ICDIP 2012), 2012, Kuala Lumpur, Malaysia
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%).
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xin He, Huiyun Jing, Xuefeng Bai, Li Li, Qi Han, and Xiamu Niu "Saliency based SIFT keypoints filtration", Proc. SPIE 8334, Fourth International Conference on Digital Image Processing (ICDIP 2012), 833415 (2 June 2012); https://doi.org/10.1117/12.946105
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Visual process modeling

Visualization

Image segmentation

Digital image processing

Image compression

Object recognition

Computer science

RELATED CONTENT


Back to Top