Zheng Shunyi

Image Relaxation Matching Based on Feature Points for DSM Generation

In photogrammetry and remote sensing, image matching is a basic and crucial process for automatic DEM generation. In this paper we presented a image relaxation matching method based on feature points. This method can be considered as an extention of regular grid point based matching. It avoids the shortcome of grid point based matching. For example, with this method, we can avoid low or even no texture area where errors frequently appear in cross correlation matching. In the mean while, it makes full use of some mature techniques such as probability relaxation, image pyramid and the like which have already been successfully used in grid point matching process. Application of the technique to DEM generaton in different regions proved that it is more reasonable and reliable.

Camera Calibration from Profile of Revolution

This paper focuses on 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, for instance, it 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 do not physically exist or calculation of fundamental matrix and Kruppa equations which can be numerically unstable, the method presented here uses 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 analyzes the relationship between the symmetry property of profile of revolution and the intrinsic parameters of a camera, and then shows 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.