Abstract
Line matching for image pairs under various transformations is a challenging task. In this paper, we present a line matching algorithm which considers both the local appearance of lines and their geometric attributes. A relational graph is built for candidate matches and a spectral technique is employed to solve this matching problem efficiently. Extensive experiments on a dataset which includes various image transformations validate the matching performance and the efficiency of the proposed line matching algorithm. © 2012 Springer-Verlag.
Cite
CITATION STYLE
Zhang, L., & Koch, R. (2012). Line matching using appearance similarities and geometric constraints. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7476 LNCS, pp. 236–245). https://doi.org/10.1007/978-3-642-32717-9_24
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