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- W2000292421 abstract "With the rapid growth of 3D technology, 3D image capture has become a critical part of the 3D feature seton mobile phones. 3D image quality is affected by the scene geometry as well as on-the-device processing. Anautomatic 3D system usually assumes known camera poses accomplished by factory calibration using a specialchart. In real life settings, pose parameters estimated by factory calibration can be negatively impacted bymovements of the lens barrel due to shaking, focusing, or camera drop. If any of these factors displaces theoptical axes of either or both cameras, vertical disparity might exceed the maximum tolerable margin and the3D user may experience eye strain or headaches. To make 3D capture more practical, one needs to considerunassisted (on arbitrary scenes) calibration. In this paper, we propose an algorithm that relies on detectionand matching of keypoints between left and right images. Frames containing erroneous matches, along withframes with insufficiently rich keypoint constellations, are detected and discarded. Roll, pitch yaw , and scaledifferences between left and right frames are then estimated. The algorithm performance is evaluated in termsof the remaining vertical disparity as compared to the maximum tolerable vertical disparity." @default.
- W2000292421 created "2016-06-24" @default.
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- W2000292421 date "2012-02-09" @default.
- W2000292421 modified "2023-09-23" @default.
- W2000292421 title "Unassisted 3D camera calibration" @default.
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- W2000292421 doi "https://doi.org/10.1117/12.909616" @default.
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