30 October 2009 A wide baseline matching method based on scale invariant feature descriptor
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Proceedings Volume 7496, MIPPR 2009: Pattern Recognition and Computer Vision; 749626 (2009) https://doi.org/10.1117/12.832419
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China
Abstract
Image matching is a fundamental aspect of many problems in computer vision. We describe a novel wide baseline matching method based on scale invariant feature descriptor. First, corners in image pairs are detected based on an improved Curvature Scale-Space (CSS) technique. These corners are relatively invariant to affine transformations, and are represented by using Scale Invariant Feature Transform (SIFT) descriptor to provide robust matching. The nearest neighbor distance is then applied to remove mismatched corners. Finally, the robust estimation algorithm, RANSAC, is adopt to estimate the fundamental matrix from the correspondence, and at the same time identify inlying matches. Experiments demonstrate the feasibility of this method.
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Jun Miao, Jun Miao, Jun Chu, Jun Chu, Guimei Zhang, Guimei Zhang, Ruina Feng, Ruina Feng, } "A wide baseline matching method based on scale invariant feature descriptor", Proc. SPIE 7496, MIPPR 2009: Pattern Recognition and Computer Vision, 749626 (30 October 2009); doi: 10.1117/12.832419; https://doi.org/10.1117/12.832419
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