Camera self-calibration technique based on hierarchical reconstruction and bundle adjustment

摘要

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.