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16 July 2019 Automatic camera pose estimation based on a flat surface map
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Proceedings Volume 11172, Fourteenth International Conference on Quality Control by Artificial Vision; 111720X (2019) https://doi.org/10.1117/12.2521780
Event: Fourteenth International Conference on Quality Control by Artificial Vision, 2019, Mulhouse, France
Abstract
This paper proposes a novel approach that performs extrinsic parameter estimation of a camera installed in a man-made environment using a single image. The problem of extrinsic parameter calibration is identical to 6DoF (six-degrees of freedom) localization problem of the camera. We take advantage of line information that is usually present in the man-made environment such as inside of the building. Our approach only requires a flat surface map for a 3D environment model which can be easily obtained from the blueprint of the artificial environment (e.g., CAD data). In order to manage the complicated 6DoF search problem, we propose a novel image descriptor defined in quantized Hough space to perform 3D-2D matching process between line features from the 3D flat surface model and the 2D single image. The proposed method can robustly estimate the complete extrinsic parameters of the camera, as we demonstrate experimentally.
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Yonghoon Ji, Atsushi Yamashita, Kazunori Umeda, and Hajime Asama "Automatic camera pose estimation based on a flat surface map", Proc. SPIE 11172, Fourteenth International Conference on Quality Control by Artificial Vision, 111720X (16 July 2019); https://doi.org/10.1117/12.2521780
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