Graph Matching by Simplified Convex-Concave Relaxation Procedure-Reference-Cited by-同舟云学术

Graph Matching by Simplified Convex-Concave Relaxation Procedure

Published:2014-03-22 Issue:3 Volume:109 Page:169-186
ISSN:0920-5691
Container-title:International Journal of Computer Vision
language:en
Short-container-title:Int J Comput Vis

Author:

Liu Zhi-Yong,Qiao Hong,Yang Xu,Hoi Steven C. H.

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/s11263-014-0707-7.pdf

Reference32 articles.

1. Blake, A., & Zisserman, A. (1987). Visual Reconstruction. Cambridge, MA, USA: MIT Press.

2. Boyd, S., & Vandenberghe, L. (2004). Convex Optimization. New York: Cambridge University Press.

3. Cho, M., Alahari, K., Ponce, J., et al. (2013). Learning graphs to match. In: ICCV 2013-IEEE International Conference on Computer Vision.

4. Cho, M., Lee, J., & Lee, K. M. (2010). Reweighted random walks for graph matching. In: Computer Vision-ECCV 2010. Berlin: Springer.

5. Cho, M., Lee, K.M. (2012). Progressive graph matching: Making a move of graphs via probabilistic voting. In: Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on, pp. 398–405. IEEE.

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