We focus on the detection of orthogonal vanishing points using line segments extracted from a single view, and using these for camera self-calibration. Recent

We focus on the estimation of radial lens distortion utilizing vanishing points detected in single images. Recent methods for vanishing point detection either ignore radial distortion completely, or assume only weak distortion, which is accounted for after vanishing point estimation. Unfortunately, if strong radial distortion is present the effects are detrimental to the extraction of vanishing points and such algorithms are bound to fail. To overcome this limitation, we suggest a closed-form solution for the problem of simultaneously estimating a single vanishing point and radial distortion from three distorted image lines. By utilizing our solver in a RANSAC-like algorithm, we arrive at a unified camera calibration approach, which in addition to stably estimating radial distortion, computes the camera's focal length if at least two orthogonal vanishing points are present. Based on extensive experiments we show that our approach presents a significant contribution to the state-of-the-art in camera self-calibration from single images.

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