Presentation + Paper
27 September 2016 Accurate estimation of principal point using three mutually orthogonal horizon lines
Abdulrahman S. Alturki, John S. Loomis
Author Affiliations +
Abstract
Accurate estimation of the principal point (PP) is critical for many camera calibration applications. Taking the PP as the intersection of the optical axis with the image plane, it is possible to identify this location as the orthocenter of three orthogonal vanishing points. This paper presents a method for accurately identifying the three vanishing points as the intersections of three horizon lines. The technique utilizes groups of images of a checkerboard test pattern collected from three orthogonal planes. Each group consists of images of the checkerboard rotated to different positions in the same plane, which can be used to identify a single horizon line. This is achieved by locating checkerboard corner points as saddle points, and using a Hough transform to group them into rows and columns. The vanishing points generated from the rows and columns lie along the same horizon line. Applying this technique to the rotated images within the group allows accurate estimation of the horizon line. Repeating this for image groups on three orthogonal planes creates horizon lines that effectively intersect at three orthogonal vanishing points, allowing for identification of the PP. The advantage of this technique is that it indirectly finds the three orthogonal vanishing points using horizon lines that are accurately found using fits to multiple vanishing points. Experiments with this technique indicate that it significantly reduces the error in finding the PP.
Conference Presentation
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Abdulrahman S. Alturki and John S. Loomis "Accurate estimation of principal point using three mutually orthogonal horizon lines", Proc. SPIE 9971, Applications of Digital Image Processing XXXIX, 997102 (27 September 2016); https://doi.org/10.1117/12.2234209
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CITATIONS
Cited by 1 scholarly publication.
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KEYWORDS
Cameras

Calibration

3D image processing

3D modeling

Image segmentation

Imaging systems

Optical spheres

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