Subspace projection technique applied to camera self-calibration and 3D reconstruction from single-view

Camera self-calibration and 3D reconstruction plays an important role in computer vision system. Based on the relationship between the null space fell by the depth vector of the target imaged in the un-calibrated single-view and the null space of the model shape matrix of the target, a linear six-point algorithm to exactly self-calibrate camera and to reconstruct the 3D pose of the imaged target from the single-view. The algorithm applies sub-space projection principle and SVD-plus-QR technique and needs at least six points to get the solution. The theoretical analysis and the experiments have demonstrated that the suggested algorithm is fast, exact, efficient and rather robust against noise.