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A comparison of SIFT, PCA-SIFT and SURF
Luo Juan, Oubong Gwun
Pages - 143 - 152     |    Revised - 30-09-2009     |    Published - 21-10-2009
Volume - 3   Issue - 4    |    Publication Date - August 2009  Table of Contents
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KEYWORDS
SIFT, , PCA-SIFT,, SURF,, robust detectors
ABSTRACT
This paper compares three robust feature detection methods, they are, Scale Invariant Feature Transform (SIFT), Principal Component Analysis (PCA) -SIFT and Speeded Up Robust Features (SURF). Lowe presented SIFT [1], which was successfully used in recognition, stitching and many other applications because of its robustness. Yan Ke [2] gave a change of SIFT by using PCA to normalize the gradient patch instead of histogram. H. Bay [3] presented a faster method for SURF, which used Fast-Hessian detector. The performance of the three methods is compared for scale changes, rotation , blur, illumination changes and affine transformations, all of which uses repeatability as an evaluation measurement. Additionally, RANSAC is used to reject the inconsistent matches [4]. SIFT presents its stability in most situation except rotation and illumination changes. SURF is the fastest one with good performance as the same as SIFT, PCA-SIFT shows its advantages in rotation, blur and illumination changes.
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434 Juan, L., & Gwun, O. (2010, July). SURF applied in panorama image stitching. In Image Processing Theory Tools and Applications (IPTA), 2010 2nd International Conference on (pp. 495-499). IEEE.
435 Chaaraoui, A. A., Climent-Pérez, P., & Flórez-Revuelta, F. (2012). A review on vision techniques applied to human behaviour analysis for ambient-assisted living. Expert Systems with Applications, 39(12), 10873-10888.
436 Shivakumar, B. L., & Baboo, L. D. S. S. (2011). Detection of region duplication forgery in digital images using SURF. IJCSI International Journal of Computer Science Issues, 8(4).
437 Fathi, H., & Brilakis, I. (2011). Automated sparse 3D point cloud generation of infrastructure using its distinctive visual features. Advanced Engineering Informatics, 25(4), 760-770.
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440 Harwin, S., & Lucieer, A. (2012). Assessing the accuracy of georeferenced point clouds produced via multi-view stereopsis from unmanned aerial vehicle (UAV) imagery. Remote Sensing, 4(6), 1573-1599.
441 Dardas, N. H., & Georganas, N. D. (2011). Real-time hand gesture detection and recognition using bag-of-features and support vector machine techniques. Instrumentation and Measurement, IEEE Transactions on, 60(11), 3592-3607.
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1 FOR JOURNALS: D. Lowe.”Distinctive Image Features from Scale-Invariant Keypoints”, IJCV, 60(2):91–110, 2004.
2 FOR CONFERENCES: Y. Ke and R. Sukthankar.PCA-SIFT: “A More Distinctive Representation for Local Image Descriptors” ,Proc. Conf. Computer Vision and Pattern Recognition, pp. 511-517, 2004.
3 FOR CONFERENCES: Bay,H,. Tuytelaars, T., &Van Gool, L.(2006). “SURF: Speeded Up Robust Features”, 9th European Conference on Computer Vision.
4 FOR CONFERENCES: K. Mikolajczyk and C. Schmid. “Indexing Based on Scale Invariant Interest Points”. Proc. Eighth Int’l Conf. Computer Vision, pp. 525-531, 2001.
5 FOR JOURNALS: K.Kanatani. “Geometric information criterion for model selection”, IJCV, 26(3):171-189,1998.
6 FOR JOURNALS: K. Mikolajzyk and C. Schmid. “A Perforance Evaluation of Local Descriptors”, IEEE,Trans. Pattern Analysis and Machine Intelligence, vol.27, no.10, pp 1615-1630, October 2005.
7 FOR JOURNALS: K. Mikolajczyk, T. Tuytelaars, C. Schmid, A. Zisserman, J. Matas, F. Schaffalitzky, T. Kadir, and L.V. Gool.” A Comparison of Affine Region Detectors”, IJCV, 65(1/2):43-72, 2005.
8 Eric Chu,Erin Hsu, Sandy Yu. “Image-Guided Tours: Fast-Approximated SIFT with U-SURF Features”, Stanford University.
9 FOR CONFERENCES: Yang zhan-long and Guo bao-long. “Image Mosaic Based On SIFT”, International Conference on Intelligent Information Hiding and Multimedia Signal Processing, pp:1422-1425,2008.
10 FOR CONFERENCES: M. Brown and D. Lowe.” Recognizing Panoramas”. Proc. Ninth Int’l Conf. Computer Vision, pp. 1218-1227, 2003.
11 FOR CONFERENCES: Salgian, A.S. “Using Multiple Patches for 3D Object Recognition”, Computer Vision and Pattern Recognition, CVPR '07. pp:1-6, June 2007.
12 FOR CONFERENCES: Y. Heo, K. Lee, and S. Lee. “Illumination and camera invariant stereo matching ”. In CVPR, pp:1–8, 2008.
13 FOR SYMPOSIUM: Kus, M.C.; Gokmen, M.; Etaner-Uyar, S. ” Traffic sign recognition using Scale Invariant Feature Transform and color classification”. ISCIS '08. pp: 1-6, Oct. 2008.
14 FOR TRANSACTIONS: Stokman, H; Gevers, T.” Selection and Fusion of Color Models for Image Feature Detection ”. Pattern Analysis and Machine Intelligence, IEEE Transactions on Volume 29, Issue 3, pp:371 – 381, March 2007.
15 FOR CONFERENCES: Cheng-Yuan Tang; Yi-Leh Wu; Maw-Kae Hor; Wen-Hung Wang. “Modified sift descriptor for image matching under interference”. Machine Learning and Cybernetics, 2008 International Conference on Volume 6, pp:3294 – 3300, July 2008.
Miss Luo Juan
- South Korea
qiuhehappy@hotmail.com
Dr. Oubong Gwun
Computer Graphics Lab, Chonbuk National University, Jeonju 561-756, South Korea - South Korea