A novel ellipse classification and relative pose estimation algorithm is presented based on surface of revolution (SOR) for multiple-ellipse images. Firstly, the contour following method is performed on images to detect ellipses. Secondly, the meaningful ellipses are obtained based on parallel constraint and vertical constraint. Finally, relative pose between the target and the camera is calculated by the meaningful ellipses. Experimental results indicate that the method performs well in ellipse classification and pose estimation. The precision of classification is higher than 97% for synthetic images corrupted by 0-16% salt-and-pepper noise. The absolute error of the pose angle is less than 1°, and the absolute errors along the depth direction and other directions are less than 80 mm and 15 mm, respectively, when the measurement distance is less than 10 m.