27 October 2013 Camera self-calibration technique based on hierarchical reconstruction and bundle adjustment
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Proceedings Volume 8919, MIPPR 2013: Pattern Recognition and Computer Vision; 89190Z (2013) https://doi.org/10.1117/12.2030720
Event: Eighth International Symposium on Multispectral Image Processing and Pattern Recognition, 2013, Wuhan, China
Abstract
Camera calibration is essential to obtaining three-dimensional information from two-dimensional image, this paper combines the method of photogrammetry and computer vision, put forward a kind of camera self-calibration based on hierarchical reconstruction and bundle adjustment. The projective reconstruction is obtained by SVD of the measurement matrix, Kruppa equation are deduced for calculating the camera parameters, then upgrade projective reconstruction to Euclidean reconstruction. Executing overall optimization to solve the inner orientation elements of the camera and the lens distortion parameters by bundle adjustment .Characteristics of this method is simple, not requested to build the field of high-precision control, just around the target for three or more images, the inner orientation elements of the camera and distortion parameters are solving ,achieving the camera self-calibration.
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Chunsen Zhang, Pengfei Fen, "Camera self-calibration technique based on hierarchical reconstruction and bundle adjustment", Proc. SPIE 8919, MIPPR 2013: Pattern Recognition and Computer Vision, 89190Z (27 October 2013); doi: 10.1117/12.2030720; https://doi.org/10.1117/12.2030720
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