Real-time camera pose estimation via line tracking

Real-time camera pose estimation via line tracking Real-time camera calibration has been intensively studied in augmented reality. However, for texture-less and texture-repeated scenes as well as poorly illuminated scenes, obtaining a stable calibration is still an open problem. In the paper, we propose a method of calibrating a live video by tracking orthogonal vanishing points. Since vanishing points cannot be obtained directly on the image, the tracking is achieved by tracking parallel lines. This is a changeling problem due to the fact that vanishing points are sensitive to image noise, camera movement, and illumination variation. We tackle the challenges by three optimization procedures and flexible process of degenerated cases. During three optimizations, several explicitly geometric constraints are incorporated, ensuring the calibration result robust to poor illumination and camera movement. A variety of challenging examples demonstrate that the proposed algorithm outperforms state-of-the-art methods for texture-less and texture-repeated scenes. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The Visual Computer Springer Journals

Real-time camera pose estimation via line tracking

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Publisher
Springer Journals
Copyright
Copyright © 2018 by Springer-Verlag GmbH Germany, part of Springer Nature
Subject
Computer Science; Computer Graphics; Computer Science, general; Artificial Intelligence (incl. Robotics); Image Processing and Computer Vision
ISSN
0178-2789
eISSN
1432-2315
D.O.I.
10.1007/s00371-018-1523-9
Publisher site
See Article on Publisher Site

Abstract

Real-time camera calibration has been intensively studied in augmented reality. However, for texture-less and texture-repeated scenes as well as poorly illuminated scenes, obtaining a stable calibration is still an open problem. In the paper, we propose a method of calibrating a live video by tracking orthogonal vanishing points. Since vanishing points cannot be obtained directly on the image, the tracking is achieved by tracking parallel lines. This is a changeling problem due to the fact that vanishing points are sensitive to image noise, camera movement, and illumination variation. We tackle the challenges by three optimization procedures and flexible process of degenerated cases. During three optimizations, several explicitly geometric constraints are incorporated, ensuring the calibration result robust to poor illumination and camera movement. A variety of challenging examples demonstrate that the proposed algorithm outperforms state-of-the-art methods for texture-less and texture-repeated scenes.

Journal

The Visual ComputerSpringer Journals

Published: May 8, 2018

References

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