Leveraging 3D City Models for Rotation Invariant Place-of-Interest Recognition-Reference-Cited by-同舟云学术

Leveraging 3D City Models for Rotation Invariant Place-of-Interest Recognition

Published:2011-05-27 Issue:3 Volume:96 Page:315-334
ISSN:0920-5691
Container-title:International Journal of Computer Vision
language:en
Short-container-title:Int J Comput Vis

Author:

Baatz Georges,Köser Kevin,Chen David,Grzeszczuk Radek,Pollefeys Marc

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/s11263-011-0458-7.pdf

Reference27 articles.

1. Baatz, G., Köser, K., Chen, D., Grzeszczuk, R., & Pollefeys, M. (2010). Handling urban location recognition as a 2D homothetic problem. In ECCV.

2. Bay, H., Ess, A., Tuytelaars, T., & Van Gool, L. (2008). SURF: Speeded Up Robust Features. Computer Vision and Image Understanding, 110(3).

3. Bishop, C. M. (2006). Pattern recognition and machine learning. ISBN 0-387-31073-8, Section 2.5.1, p. 123.

4. Cao, Y., & McDonald, J. (2009). Viewpoint invariant features from single images using 3D geometry. In IEEE Workshop on Applications of Computer Vision.

5. Chandrasekhar, V., Takacs, G., Chen, D., Tsai, S., Grzeszczuk, R., & Girod, B. (2009). CHoG: compressed histogram of gradients. In CVPR.

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