We present an approach to enhance the accuracy of structure from motion (SfM) in the two-view case. We first answer the question: "fewer data with higher accuracy, or more data with less accuracy?" For this, we establish a relation between SfM errors and a function of the number of matches and their epipolar errors. Using an accuracy estimator of individual matches, we then propose a method to select a subset of matches that has a good quality vs. quantity compromise. We also propose a variant of least squares matching to refine match locations based on a focused grid and a multi-scale exploration. Experiments show that both selection and refinement contribute independently to a better accuracy. Their combination reduces errors by a factor of 1.1 to 2.0 for rotation, and 1.6 to 3.8 for translation. © 2014 Springer International Publishing.
CITATION STYLE
Liu, Z., Monasse, P., & Marlet, R. (2014). Match selection and refinement for highly accurate two-view structure from motion. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8690 LNCS, pp. 818–833). Springer Verlag. https://doi.org/10.1007/978-3-319-10605-2_53
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