Attributed Graph Matching for Image-Features Association Using SIFT Descriptors
Image-features matching based on SIFT descriptors is subject to the misplacement of certain matches due to the local nature of the SIFT representations. Some well-known outlier rejectors aim to remove those misplaced matches by imposing geometrical consistency. We present two graph matching approaches (one continuous and one discrete) aimed at the matching of SIFT features in a geometrically consistent way. The two main novelties are that, both local and contextual coherence are imposed during the optimization process and, a model of structural consistency is presented that accounts for the quality rather than the quantity of the surrounding matches. Experimental results show that our methods achieve good results under various types of noise.
Keywordsattributed graph matching SIFT image registration discrete labeling softassign
- 2.Lowe, D.G.: Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision 60(2) (January 2004)Google Scholar
- 5.Gold, S., Rangarajan, A.: A graduated assignment algorithm for graph matching. IEEE Transactions on Pattern Analysis and Machine Intelligence 18(4) (April 1996)Google Scholar
- 6.Waltz, D.: Understanding line drawings of scenes with shadows. In: The Psychology of Computer Vision, McGraw-Hill, New York (1975)Google Scholar
- 8.Luo, B., Hancock, E.R.: Structural graph matching using the em algorithm and singular value decomposition. IEEE Transactions on Pattern Analysis and Machine Intelligence 23(10) (October 2001)Google Scholar
- 9.Rosenfeld, A., Hummel, R.A., Zucker, S.W.: Scene labelling by relaxation operations. IEEE Transactions on Systems, Man and Cybernetics (6), 420–433 (1976)Google Scholar