Recursive Structure from Motion Using Hybrid Matching Constraints with Error Feedback

We propose an algorithm for recursive estimation of structure and motion in rigid body perspective dynamic systems, based on the novel concept of continuous-differential matching constraints for the estimation of the velocity parameters. The parameter estimation procedure is fused with a continuous-discrete extended Kalman filter for the state estimation. Also, the structure and motion estimation processes are connected by a reprojection error constraint, where feedback of the structure estimates is used to recursively obtain corrections to the motion parameters, leading to more accurate estimates and a more robust performance of the method. The main advantages of the presented algorithm are that after initialization, only three observed object point correspondences between consecutive pairs of views are required for the sequential motion estimation, and that both the parameter update and the correction step are performed using linear constraints only. Simulated experiments are provided to demonstrate the performance of the method.