Abstract
A robust and successful learning methodology based on sequential Relevance Vector Machine Regression (RVR) for identifying correct matches and mismatches from initial SIFT matching points is proposed. We introduce a nonlinear matching function between the corresponding points set from the given image pairs. The sequential RVR algorithm is used to learn the matching function relationship; correct matches and mismatches can be detected by checking the residuals whether they are consistent with the matching function models. Experiments show that the proposed method can efficiently pick out the mismatches and preserve the correct matches, especially on the larger view angle matching condition, and outperforms to state-of-the art approaches.
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