Robust two-view external calibration by combining lines and scale invariant point features

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Abstract

In this paper we present a new approach for automatic external calibration for two camera views under general motion based on both line and point features. Detected lines are classified into two classes: either vertical or horizontal. We make use of these lines extensively to determine the camera pose. First, the rotation is estimated directly from line features using a novel algorithm. Then normalized point features are used to compute the translation based on epipolar constraint. Compared with point-feature-based approaches, the proposed method can handle well images with little texture. Also, our method bypasses sophisticated post-processing stage that is typically employed by other line-feature-based approaches. Experiments show that, although our approach is simple to implement, the performance is reliable in practice. © Springer-Verlag Berlin Heidelberg 2008.

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APA

Zhang, X., Zhou, J., & Li, B. (2008). Robust two-view external calibration by combining lines and scale invariant point features. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5358 LNCS, pp. 825–835). https://doi.org/10.1007/978-3-540-89639-5_79

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