Scale Invariant Feature Transform on the Sphere: Theory and Applications-Reference-Cited by-同舟云学术

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Scale Invariant Feature Transform on the Sphere: Theory and Applications

Published:2011-11-10 Issue:2 Volume:98 Page:217-241
ISSN:0920-5691
Container-title:International Journal of Computer Vision
language:en
Short-container-title:Int J Comput Vis

Author:

Cruz-Mota Javier,Bogdanova Iva,Paquier Benoît,Bierlaire Michel,Thiran Jean-Philippe

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Link

http://link.springer.com/content/pdf/10.1007/s11263-011-0505-4.pdf

Reference40 articles.

1. Barut, A. O., & Ra̧czka, R. (1986). Theory of group representations and applications (2nd edn.). Singapore: World Scientific. ISBN 9971502178.

2. Baumberg, A. (2000). Reliable feature matching across widely separated views. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 774–781).

3. Bay, H., Ess, A., Tuytelaars, T., & Van Gool, L. (2008). Speeded-up robust features (SURF). Computer Vision and Image Understanding, 110(3), 346–359. http://www.sciencedirect.com/science/article/B6WCX-4RC2S4T-2/1/cddc9c43940bd8fb62d6ed668de29e20 .

4. Bogdanova, I., Bresson, X., Thiran, J. P., & Vandergheynst, P. (2007). Scale-space analysis and active contours for omnidirectional images. IEEE Transactions on Image Processing, 16(7), 1888–1901.

5. Boult, T. E., Micheals, R. J., Gao, X., & Eckmann, M. (2001). Into the woods: visual surveillance of noncooperative and camouflaged targets in complex outdoor settings. Proceedings of the IEEE, 89(10), 1382–1402. doi: 10.1109/5.959337 .

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