We present an approach for two-view motion segmentation for freely moving cameras, by formulating the epipolar constraint and spacial consistency into a discrete energy minimization problem, which can be efficiently solved using graph cut algorithms. With dense optical flow and proper sampling, a set of matched points is acquired for computing the fundamental matrix and the corresponding epipolar lines. The points distance to the epipolar lines, and their position on the image plane are used to construct a Markov Random Field (MRF) with discrete label-space. The 2-dimension label-space, i.e. motion area or static area, is computed using graph cut algorithms. We demonstrate the effectiveness of our method with the Johns Hopkins 155 motion dataset.