A theory of self-calibration of a moving camera
International Journal of Computer Vision
Kruppa's Equations Derived from the Fundamental Matrix
IEEE Transactions on Pattern Analysis and Machine Intelligence
Euclidean 3D Reconstruction from Image Sequences with Variable Focal Lenghts
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Euclidean 3D Reconstruction from Stereo Sequences with Variable Focal Lengths
ACCV '95 Invited Session Papers from the Second Asian Conference on Computer Vision: Recent Developments in Computer Vision
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
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Camera self-calibration is one of the key technologies in 3D reconstruction. In this paper a new Camera Self-Calibration method is proposed which is based on image sequence, in addition, the intrinsic camera parameters are varying. This method based on Kruppa equations, by two upper triangular matrixes must exist a relational matrix, make the varying focal length convert to the relational matrix, thus use the epipolar geometry relationship of absolute conic to get the intrinsic camera parameters. Experimental results show that the method is a high precision, robustness strong self ---calibration.