Camera calibration is the process of determining the intrinsic or internal parameters (i.e. focal length and principal point) of a camera, and is important for both motion estimation and metric reconstruction of 3D models. This paper addresses the problem of calibrating a pinhole camera from images of profile of a revolution. In this paper, the symmetry of images of profiles of revolution has been extensively exploited and a practical and accurate technique of camera calibration from profiles alone has been developed. Compared with traditional techniques for camera calibration which may involve taking images of some precisely machined calibration pattern (such as a calibration grid), or edge detection for determining vanish points which are often far from images center or even don't physically exist, or calculation of fundamental matrix and Kruppa equations which can be numerically unstable, the method presented here used just profiles of revolution, which are commonly found in daily life (e.g. bowls and vases), to make the process easier as a result of the reduced cost and increased accessibility of the calibration objects. This paper firstly analyzed the relationship between the symmetry property of profile of revolution and the intrinsic parameters of a camera, and then showed how to use images of profile of revolution to provide enough information for determining intrinsic parameters. During the process, high-accurate profile extraction algorithm has also been used. Finally, results from real data are presented, demonstrating the efficiency and accuracy of the proposed methods.