1 |
D. Lowe, “Distinctive image features from scaleinvariant keypoints,” International Journal of Computer Vision, Vol. 60, No. 2, pp. 91-110, 2004.
DOI
|
2 |
J. Sivic, and A. Zisserman, "Video Google: a text retrieval approach to object matching in videos," Proc. of the IEEE International Conference on Computer Vision 2003, pp. 1470-1477, 2003.
|
3 |
E. Rosten, and T. Drummond, "Machine learning for high-speed corner detection," Proc. of the European Conference on Computer Vision 2006, pp. 430-443, 2006.
|
4 |
M. Calonder, V. Lepetit, C. Strecha, and P. Fua, "BRIEF: binary robust independent elementary features," Proc. of the European Conference on Computer Vision 2010, pp. 5-11, 2010.
|
5 |
E. Rublee, V. Rabaud, K. Konolige, and G. Bradski, "ORB: an efficient alternative to SIFT or SURF," Proc. of the International Conference on Computer Vision 2011, pp. 2564-2571, 2011.
|
6 |
S. Leutenegger, M. Chli, and R. Siegwart, "BRISK: Binary robust invariant scalable keypoints," Proc. of the International Conference on Computer Vision 2011, pp. 2548-2555, 2011.
|
7 |
A. Alahi, R. Ortiz, and P. Vandergheynst, "FREAK: Fast Retina Keypoint," Proc. of the IEEE Conference on Computer Vision and Pattern Recognition 2012, pp. 510-517, 2012.
|
8 |
D. Arthur, and S. Vassilvitskii, "k-means++: the advantages of careful seeding," Proc. of the 18th annual ACM-SIAM symposium on Discrete algorithms 2007, pp. 1027-1035, 2007.
|
9 |
D. Nister, and H. Stewenius, "Scalable recognition with a vocabulary tree," Proc. of the IEEE Conference on Computer Vision and Pattern Recognition 2006, pp. 2161-2168, 2006.
|