A linear algorithm for motion estimation using parallel-line-segment correspondences
平行线段对应的运动估计线性算法

We investigate the motion estimation from image sequence features, and propose for it a linear algorithm based on the parallel-line-segment(PLS) correspondences. The line segment is represented by two elements: end points and the line in between. The space line segment structure is reconstructed step by step from image lines, using the principle of parallelism. Then, the two elements of a space line segment are established based on the motion parameter equations which are solved by using the screw theory and quaternion. Finally, the motion parameters are optimized by the particle swarm optimization(PSO) algorithm. Our algorithm needs at least two lines and two perspective views to obtain the parameters; thus, the multisolution phenomenon is avoided and the magnitude of the translation is estimated with high computation efficiency. Simulations and real experiments illustrate the effectiveness of the proposed algorithm.