It is proposed that a novel registration method for automatic co-registration of unmanned aerial vehicle (UAV) images sequence and laser point clouds. Firstly, contours of building roofs are extracted from the images sequence and laser point clouds using marked point process and local salient region detection, respectively. The contours from each data are matched via back-project proximity. Secondly, the exterior orientations of the images are recovered using a linear solver based on the contours corner pairs followed by a co-planar optimization which is implicated by the matched lines form contours pairs. Finally, the exterior orientation parameters of images are further optimized by matching 3D points generated from images sequence and laser point clouds using an iterative near the point (ICP) algorithm with relative movement threshold constraint. Experiments are undertaken to check the validity and effectiveness of the proposed method. The results show that the proposed method achieves high-precision co-registration of low-altitude UAV image sequence and laser points cloud robustly. The accuracy of the co-produced DOMs meets 1:500 scale standards.