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Automatic camera pose estimation based on a flat surface map
Author(s): Yonghoon Ji; Atsushi Yamashita; Kazunori Umeda; Hajime Asama
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Paper 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.

Paper Details

Date Published: 16 July 2019
PDF: 6 pages
Proc. SPIE 11172, Fourteenth International Conference on Quality Control by Artificial Vision, 111720X (16 July 2019); doi: 10.1117/12.2521780
Show Author Affiliations
Yonghoon Ji, Chuo Univ. (Japan)
Atsushi Yamashita, The Univ. of Tokyo (Japan)
Kazunori Umeda, Chuo Univ. (Japan)
Hajime Asama, The Univ. of Tokyo (Japan)


Published in SPIE Proceedings Vol. 11172:
Fourteenth International Conference on Quality Control by Artificial Vision
Christophe Cudel; Stéphane Bazeille; Nicolas Verrier, Editor(s)

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