Sift keypoint removal via convex relaxation
Cheng A.; Li Y.; Zhou J.
Conference NameIEEE International Conference on Multimedia & Expo (ICME)
Source PublicationProceedings - IEEE International Conference on Multimedia and Expo
Conference DateJUN 29-JUL 03, 2015
Conference PlaceTurin, ITALY

Due to the high robustness against various image transformations, Scale Invariant Feature Transform (SIFT) has been widely employed in many computer vision and multimedia security areas to extract image local features. Though SIFT has been extensively studied from various perspectives, its security against malicious attack has rarely been addressed. In this work, we demonstrate that the SIFT keypoints can be effectively removed, without introducing serious distortion on the image. This is achieved by formulating the SIFT keypoint removal as a constrained optimization problem, where the constraints are well-designed to suppress the existence of local extremum and prevent generating new keypoints within a local cuboid in the scale space. We show that such optimization problem in the ideal case is non-convex. To make the computation feasible, we propose a relaxation technique to convexify the original problem, while maximally preserving the solution space. As demonstrated experimentally, our proposed SIFT removal algorithm significantly outperforms the state-of-the-arts in terms of keypoint removal rate-distortion (KRR-D) performance. Our results imply that an authorization mechanism is required for SIFT-based systems to verify the validity of the input data, so as to achieve high reliability.

KeywordConvex Optimization Convex Relaxation Keypoint Removal Sift
URLView the original
Indexed BySCI
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Software Engineering ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS IDWOS:000380486500046
Fulltext Access
Citation statistics
Cited Times [WOS]:0   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
AffiliationUniversidade de Macau
Recommended Citation
GB/T 7714
Cheng A.,Li Y.,Zhou J.. Sift keypoint removal via convex relaxation[C],2015.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Cheng A.]'s Articles
[Li Y.]'s Articles
[Zhou J.]'s Articles
Baidu academic
Similar articles in Baidu academic
[Cheng A.]'s Articles
[Li Y.]'s Articles
[Zhou J.]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Cheng A.]'s Articles
[Li Y.]'s Articles
[Zhou J.]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.