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In order to determine camera parameters, a calibration procedure involving the camera recordings of a checkerboard is usually performed. In this paper, we propose an alternative approach that uses Gray-code patterns displayed on an LCD screen. Gray-code patterns allow us to decode 3D location information of points of the LCD screen at every pixel in the camera image. This is in contrast to checkerboard patterns where the number of corresponding locations is limited to the number of checkerboard corners. We show that, for the case of a UEye CMOS camera, the precision of focal-length estimation is 1.5 times more precise than when using a standard calibration with a checkerboard pattern.
Pubmed ID: 30634616
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Computer vision and machine learning software library which provides a common infrastructure for computer vision applications. The algorithms within the library can be used to detect and recognize faces, identify objects, classify human actions in videos, track camera movements and moving objects, extract 3D models of objects, produce 3D point clouds from stereo cameras, stitch images together to produce a high resolution image of an entire scene, find similar images from an image database, and follow eye movements, recognize scenery and establish markers to overlay it with augmented reality. It has C++, C, Python, Java and MATLAB interfaces.
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