Camera pose estimation algorithm based on point correspondence is lack of scientific performance evaluation method, which increases the selection difficulty for algorithms in the engineering applications. Aimed at the problem, the evaluation strategy for camera pose estimation algorithm under specific cost function is put forward, mainly including three performance evaluation parameters: precision, efficiency and success rate of domain optimal solution. Domain optimal solution is different from local optimal solution. If a given area is at the definition domain of cost function, the optimal solution of this area is equivalent to the global optimal solution. The judgment method of domain optimal solution is described emphatically, the cost function is set up based on angle residual, and the lower bound Hessian matrix of cost function is calculated using attitude matrix. If lower bound of Hessian matrix is positive semi-definite, the cost function is convex function in the neighborhood that centers on pose matrix and the size is confirmed by the image point noise model. There exists optimal solution in given domain. In virtue of simulation experimental platform, nine classical camera pose estimation algorithms performance are evaluated. Results indicate that the comprehensive performance of RPnP+LHM method is the best.