This work addresses the challenge of obtaining world coordinates when estimating the pose of curved objects through monocular vision. An efficient method for estimating the pose of curved objects is proposed herein. The proposed method combines binocular vision with the cooperative target. A point cloud of the target object in various poses is generated using a binocular camera in order to rapidly extract the world coordinates of the corner points of the target. Unlike the traditional point-cloud registration pose-estimation methods, the mean value of the corresponding point coordinate difference is used to represent the translation vector in the proposed method. The normal vector of the tangent plane comprising the target corner points is used to form a matrix of the target coordinates in different poses; thus, the rotation matrix is derived. The proposed method not only ensures the accuracy and stability of the pose estimation results but also improves the efficiency of the algorithm significantly. The experimental results show that the efficiency of the proposed method is 98.24% and 97.58% higher than those of the ICP algorithm and NDT algorithm, respectively. The proposed method to estimate the pose of curved objects has various practical applications that are reviewed in this work.