In this paper

we introduce a new algorithm for estimating camera pose from point correspondences.Generally

the camera pose problem could be formulated as an optimization problem.The current methods transform the problem into a set of second order cone programming (SOCP) feasibility problems which obtain the global optimal solution by searching the rotation space.In this paper

by relaxing the second-order cone constraints to linear constraints

we propose an improved method that combines branching and bounding with linear programming (LP).Our method cannot only get the global optimal pose but also runs two times faster than the curreut best method.Our approach has been tested on a number of synthetically generated and real data sets

and the results demonstrate the accuracy and the high speed of the proposed method.