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Mathematical Problems in Engineering
Volume 2012 (2012), Article ID 382369, 14 pages
Multiscale Point Correspondence Using Feature Distribution and Frequency Domain Alignment
1School of Control Science and Engineering, Shandong University, Jinan 250061, China
2College of Information and Electrical Engineering, Shandong University of Science and Technology, Qingdao 266590, China
3State Key Lab of Intelligent Technologies and Systems, Tsinghua National Laboratory for Information Science and Technology (TNList), Department of Automation, Tsinghua University, Beijing 100084, China
Received 23 July 2012; Revised 19 November 2012; Accepted 20 November 2012
Academic Editor: Asier Ibeas
Copyright © 2012 Zeng-Shun Zhao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- M. Z. Brown, D. Burschka, and G. D. Hager, “Advances in computational stereo,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25, no. 8, pp. 993–1008, 2003.
- Y. Bentoutou, N. Taleb, K. Kpalma, and J. Ronsin, “An automatic image registration for applications in remote sensing,” IEEE Transactions on Geoscience and Remote Sensing, vol. 43, no. 9, pp. 2127–2137, 2005.
- P. Thévenaz, U. E. Ruttimann, and M. Unser, “A pyramid approach to subpixel registration based on intensity,” IEEE Transactions on Image Processing, vol. 7, no. 1, pp. 27–41, 1998.
- H. Foroosh, J. B. Zerubia, and M. Berthod, “Extension of phase correlation to subpixel registration,” IEEE Transactions on Image Processing, vol. 11, no. 3, pp. 188–200, 2002.
- B. S. Reddy and B. N. Chatterji, “An FFT-based technique for translation, rotation, and scale-invariant image registration,” IEEE Transactions on Image Processing, vol. 5, no. 8, pp. 1266–1271, 1996.
- K. Mikolajczyk and C. Schmid, “A performance evaluation of local descriptors,” in Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition, pp. II257–II263, June 2003.
- D. G. Lowe, “Distinctive image features from scale-invariant keypoints,” International Journal of Computer Vision, vol. 60, no. 2, pp. 91–110, 2004.
- R. Fergus, P. Perona, and A. Zisserman, “Object class recognition by unsupervised scale-invariant learning,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR '03), pp. II 264–II 271, June 2003.
- H. Bay, A. Ess, T. Tuytelaars, and L. V. Gool, “SURF: speeded up robust features,” Computer Vision and Image Understanding, vol. 110, no. 3, pp. 346–359, 2008.
- S. Gauglitz, “Evaluation of interest point detectors and feature descriptors for visual tracking,” International Journal of Computer Vision, vol. 94, no. 3, pp. 335–360, 2011.
- R. N. Bracewell, K. Y. Chang, A. K. Jha, and Y. H. Wang, “Affine theorem for two-dimensional Fourier transform,” Electronics Letters, vol. 29, no. 3, article 304, 1993.
- G. Hager and K. Toyama, “Xvision: combining image warping and geometric constraints for fast visual tracking,” in Proceedings of the 4th European Conference on Computer Vision, pp. 507–517, 1996.
- Y. Keller, A. Averbuch, and M. Israeli, “Pseudopolar-based estimation of large translations, rotations, and scalings in images,” IEEE Transactions on Image Processing, vol. 14, no. 1, pp. 12–22, 2005.
- P. Vandewalle, S. Süsstrunk, and M. Vetterll, “A frequency domain approach to registration of aliased images with application to super-resolution,” Eurasip Journal on Applied Signal Processing, vol. 2006, p. 233, 2006.
- R. Szeliski and J. Coughlan, “Hierarchical spline-based image registration,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 194–201, June 1994.
- A. A. Cole-Rhodes, K. L. Johnson, J. Lemoigne, et al., “Multiresolution registration of remote sensing imagery by optimization of mutual information using a stochastic gradient,” IEEE Transactions on Image Processing, vol. 12, no. 12, pp. 1495–1511, 2003.
- M. A. Fischler and R. C. Bolles, “Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography,” Communications of the Association for Computing Machinery, vol. 24, no. 6, pp. 381–395, 1981.
- Z.-S. Zhao, Q.-J. Tian, J.-Z. Wang, and J.-M. Zhou, “Image match using distribution of colorful SIFT,” in International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR '10), pp. 150–153, 2010.