Fish-eye lens camera no-linear calibration for stereo vision system

This paper presents an approach to calibrating a fish-eye lens camera with high accuracy for stereo vision to recover dense depth image. The camera model accounts for the fish-eye deformation and major sources of camera distortion including radial distortion, decentering distortion and thin prism distortion. We use nonlinear. least-squares techniques to solve for the camera parameters that best project three-dimensional points of a calibration pattern onto intensity edges hi an image of this pattern, without explicitly extracting the features such as corners, edges or points. The effectiveness of the proposed calibration method has beer? proved by experimentation.