Study On Uncalibrated CCD Camera Based Digital Close- Range Photogrammetry For 3D Structure Deformation Measurement

High precision three-dimensional(3D) reconstruction and vision metrology are one of the most active research areas in Computer Vision and Digital Close-range Photogrammetry society. In the large-size model experiment of civil engineering and mechanics,displacement or deformation measurement is indispensable, dial indicators and other displacement sensors are the traditional tools used for displacement measurement, but it is a contacted approaches and only with the capacity of one-dimensional measurement, so it can not work well in most cases. Photogrammetry is a non-contacted, high accuracy and automation techniques for 3D measurement which could be utilized as an effective tools in these fields, traditional photogrammetry relied on professional metric camera and other expensive facilities, But nowadays, with the development of high resolution Charged Coupled Device(CCD) solid state camera, it is widely used in close-range photogrammetry society instead of professional cameras, so the new theories and approaches are needed. Under this background, this paper studies on the uncalibrated CCD camera based digital close-range photogrammetry for 3D structure deformation measurement without enough information about object space. The contents of this paper are given as follows:1. Camera models used in computer vision and photogrammetry society are compared in thesis, The linear and nonlinear pinhole camera in computer are the same as the collinear equation with or without lens distortion. The mathematical model, resolution algorithms, applicable situations of the analytical approaches on photogrammetry such as direct linear transform, spatial resection and intersection, relation orientation and orientation and bundle adjustment are introduced, and the epipolar constraints, fundamental matrix, essential matrix and homography matrix on computer vision are introduced as well. As the fundamental matrix is the unique information which can be recovered from the uncalibrated image sequences without any prior information of object space, a new estimation algorithm named constrained robust least square method for fundamental matrix is given.2. A practical approach for point feature extraction, precise location and matching is proposed for close-range image sequences. With this approaches, the artifical coded targets are automatic detected, and the sub-pixel edges are accurately extracted with moment and curve preserving method and the accurate center are obtained with least square fitting, then the epipolar line of any two overlapped images are recovered, the LSM matching with epipolar constraints is applied for accurate feature location, and manual measurement on screen are designed if necessary. The error sources and the theoretic precisions of each measurement approach are analyzed;3. Unit quaternion are proposed for representing rotation matrix instead of traditional Euler angles, and the transformations of each representing approaches are also given. The full estimation approaches on relative orientation, absolute orientation and bundle adjustment are proposed. An improvement on PH algorithm in relative orientation are made, with this algorithm, the iterative procedures could be global convergent without any initial values. The unit-quaternion based closed-form solution for absolute orientation is a least square solution without initial values.4. 3D metric reconstruction methods with two or multiple uncalibrated views without any scene knowledge are studied, a practical quaternion based iterative algorithm for general relative orientation are proposed for two-view metric reconstruction, compared with the existed direct approaches, robustness and accuracy are improved. And a stratification 3D reconstruction method in computer are introduced to photogrammtry for interior and exterior parameters estimation, which is very helpful to initial orientation parameters estimation;5. The single station pure rotation based self-calibration approaches are studied, compared with the existed two- step estimation method, a LSM method based on explicit parameters model are proposed for self-calibration, which could improve the stability and accuracy greatly. The projection model under the assumption of camera mounted on a tripod undergoes pan-tilt-zoom(PTZ) motion with rotation eccentricity are given, and the 3D measurement of PTZ camera includes single-station relative orientation, base image extending, two-station relative orientation and absolute orientation. Where single-station relative orientation is an innovation for traditional photogrammetry, it can achieve more accuracy and need less point correspondences, and improve the geometry configuration for image sequences, which is very useful for large structures 3D measurement;6. Self-calibration bundle adjustment method is the most precise analytical method for photogrammetry and high precision 3D measurement usually uses this method for refinement when initial values are known. A unified self-calibration bundle adjustment model with datum constraints is given, which is not only appropriate for traditional photogrammetry network adjustment but for free-network. Deformation data analysis is an important task for deformation monitoring, an error ellipsoid based hypothesis test method and a wavelet based denoising method are proposed for deformation data analysis;7. Photogrammetry based 3D measurement is a non-contacted, high-efficient technique for displacement measurement, which is indispensable for some special situations.Under the background of structure displacement measurement, a Matlab program is developed. And two experiments are given for verifying the results of displacement measurements.