Real-time motion analysis with linear programming

A method to compute motion models in real time from point-to-line correspon dences using linear programming is presented. Point-to-line correspondences are the most reliable measurements for image motion given the aperture eff ect. and it is shown how they can approximate other motion measurements as well. An error measure for image alignment using the L-1 metric and based o n point-to-line correspondences achieves results which are more robust than those for the commonly used L-2 metric. The L-1 error measure is minimized using linear programming. While estimators based on L-1 are not robust in the breakdown point sense, experiments show that the proposed method is rob ust enough to allow accurate motion recovery over hundreds of consecutive f rames. The L-1 solution is compared to standard M-estimators and Least Medi an of Squares (LMedS) and it is shown that the L-1 metric provides a reason able and efficient compromise for various scenarios. The entire computation is performed in real-time on a PC without special hardware. (C) 2000 Acade mic Press.