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Proceedings Paper

Unassisted 3D camera calibration
Author(s): Kalin Atanassov; Vikas Ramachandra; James Nash; Sergio R. Goma
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Paper Abstract

With the rapid growth of 3D technology, 3D image capture has become a critical part of the 3D feature set on mobile phones. 3D image quality is affected by the scene geometry as well as on-the-device processing. An automatic 3D system usually assumes known camera poses accomplished by factory calibration using a special chart. In real life settings, pose parameters estimated by factory calibration can be negatively impacted by movements of the lens barrel due to shaking, focusing, or camera drop. If any of these factors displaces the optical axes of either or both cameras, vertical disparity might exceed the maximum tolerable margin and the 3D user may experience eye strain or headaches. To make 3D capture more practical, one needs to consider unassisted (on arbitrary scenes) calibration. In this paper, we propose an algorithm that relies on detection and matching of keypoints between left and right images. Frames containing erroneous matches, along with frames with insufficiently rich keypoint constellations, are detected and discarded. Roll, pitch yaw , and scale differences between left and right frames are then estimated. The algorithm performance is evaluated in terms of the remaining vertical disparity as compared to the maximum tolerable vertical disparity.

Paper Details

Date Published: 24 February 2012
PDF: 9 pages
Proc. SPIE 8288, Stereoscopic Displays and Applications XXIII, 828808 (24 February 2012); doi: 10.1117/12.909616
Show Author Affiliations
Kalin Atanassov, Qualcomm Inc. (United States)
Vikas Ramachandra, Qualcomm Inc. (United States)
James Nash, Qualcomm Inc. (United States)
Sergio R. Goma, Qualcomm Inc. (United States)


Published in SPIE Proceedings Vol. 8288:
Stereoscopic Displays and Applications XXIII
Andrew J. Woods; Nicolas S. Holliman; Gregg E. Favalora, Editor(s)

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