The five-point algorithm of essential matrix is a common way to achieve relative orientation of the two-view images in 3D measuring. Polynomial solving techniques, which lead to polysemia while computing, are always adopted during the computing process. In order to determine the right solution, two improved methods for five-point algorithm are proposed to avoid multi-solutions. First of all, the inconsistent solutions of physical model were excluded with cheirality constraint. Secondly, the rest error solutions can be solved by computing sums of Sampson distance of all the common points or re-projection residual. In the two-view images, the minimum value among sums is just the correct orientation parameter values. Both simulation and real images experiments have proved the feasibility and correctness of the two tactics. In most cases, methods based on Sampson are much quicker than that based on re-projection.