Research On Networked Videometrics For The Shape And Deformation Of Large-scale Structure

With the development of science and technology, more and more large-scalestructures come into our lives, such as bridge, tunnel, airplane, airship, wind turbineblade and antenna, etc. It’s a basic requirement of corresponding dynamic performanceexperiment and quality monitoring to measure the shape and deformation of theselarge-scale structures universally and dynamically with high precision.Compared with other measuring means, videometrics has a lot of advantages in thedeformation measurement of large-scale structure, it can conduct non-contact dynamicmeasurement with high precision, and can handle large set of points simultaneously. Butdeformation measurement of large-scale structure has requirement on measuring scaleand precision at the same time, that is the large field of view and high spatial resolutionrespectively, which brings contradiction for dual-camera videometrics. To cope with thisproblem, networked videometrics is proposed in this dissertation, and fourcorresponding critical problems are studied: camera network optimization, cameracalibration with high precision, real-time3D intersection and rapid bundle adjustment.Main contributions of this dissertation are as follows:1. Videometric network design based on improved genetic algorithm is proposed.The structure to be measured is quite complex, besides, cameras to be used innetworked videometrics are many and versatile, and there are a lot of environmentalrestrictions, so the optimal measuring accuracy given the amount of camera cannot beguaranteed only by experience. Thus, the first problem that has to be solved is todetermine the layout of cameras, given the model to be measured, along with the typeand the amount of camera and environmental restrictions, in order to achieve therequired measuring accuracy, and this procedure is so called videometric networkdesign.For videometric network design is a computationally exhausting nonlinearprocedure with multiple parameters and constraints, improved genetic algorithm isadopted in this dissertation to search for global optimum randomly. Kinds of factors,such as visibility, measurability and block reverse error precision estimation, etc. areconsidered in the algorithm, design results satisfying the constraining conditions andmeasuring accuracy are acquired, which can provide reliable reference for conductingfield networked measurement.2. A series of camera calibration methods is proposed for networked videometrics.Since multiple cameras are used in networked videometrics, there are adequatemultiple view geometric constraints. Self calibration result based on two views can beadopted as initial values for networked videometrics system, followed by bundleadjustment to obtain calibration result with high precision. Besides, to cope withcoupling among each parameter in camera calibration, stepwise camera calibrationmethod is studied. Sometimes, it is difficult to locate large set of control points in the area to be measured, to cope with this, flexible calibration method for large field ofview camera is studied. As a beneficial supplement to fixed camera, Theodolite-cameracan conduct full field of view measurement with high precision, correspondingcalibration method when using theodolite-camera for middle-field and far-fieldmeasurement is studied.2.1A camera self calibration method for two-view with varying focal length, whichis originated from simplified analytical solution of equivalent focal length, is proposed.Given only aspect ratio and zero-skew, this method can get the simplifiedanalytical solution of equivalent focal length from corresponding points of two images,and then cameras are calibrated and Euclidean structure is reconstructed further.2.2A stepwise camera calibration method based on pose estimation variation isproposed.In this method, first equivalent focal length is determined based on pose estimationvariation, and then other parameters are determined step by step. This method caneffectively avoid coupling among each camera parameter, in which way the value ofeach parameter can match its own physical meaning pretty well, and can be usedindependently.2.3A calibration method for large field of view camera based on infinitehomography is proposed.This method only needs approximate position of the camera and at least fournon-collinear control points to compute the infinite homography. A coordinatetransformation method is also proposed to ensure stability of the linear solution andoptimization process of the infinite homography.2.4Imaging model and high precision calibration method for quasi-concentricgeneral theodolite-camera is proposed.As for general theodolite-camera, it can be calibrated by hand-eye calibrationmethod when used for near-field measurement, if there are adequate control points in asingle image, which is not suitable for middle-field and far-field use. In order toexpediently calibrate the theodolite-camera used for middle-field and far-fieldmeasurement, we suppose the optical center of camera is quasi-concentric with therotation center of rotation frame, and its corresponding imaging model and highprecision calibration method is proposed.3. A linear intersection method, which minimizes the spatial distance, is proposed.As for the intersection, although the iterative method can guarantee accuracy, it iscomputationally expensive and cannot guarantee efficiency. Proposed method is linear,in which the geometric meanings of intersection equation is to minimize the sum ofsquares of the spatial distances from the object point to the back-projected radial of itseach corresponding image points. Only one-step resolvent is demanded, and themeasuring accuracy is very approximate to the ones of iterative method.4. Two bundle adjustment methods are proposed. One is the sparse LM indirect bundle adjustment with the form as mutual internal parameter, multiple view and objectpoints. Another is the sparse LM indirect bundle adjustment with restricted condition.Bundle adjustment is an imperative procedure to refine measuring results, in whichthe sparse block mechanism can speed the adjustment procedure up significantly, andconsidering existing restricted condition should be in accordance with the true physicalmeanings. The first method is applicable for the calibration of cameras with the samefixed internal parameters and can optimize the positions of the reference pointssimultaneously, it is suitable for camera calibration under situations in which theaccuracy of reference points is not good enough. The second method can easily set theparameters whether be adjusted or not, and can add various constraints such as intrinsicconstraint, scene constraint and motion constraint. Besides, it still preserves sparseblock structure, so it is applicable for the deformation measurement of large-scalestructure which has various constraints.Utilizing above research achievements, we have designed and developed apractical networked videometrics system for the deformation measurement oflarge-scale structure, and applied it to practical deformation measurement of windturbine blade, airplane wing and airship, etc. This system can measure the integraldeformation and all of the local deformation. The system is applicable for thecalibration and measurement of large field of view camera in simplex scene, and for themeasurement of regions without any control information for calibration.Networked videometrics method provides a powerful theoretical and technicalsupport for real-time/quasi real-time, dynamic and high precision measurement oflarge-scale structure deformation. It effectively expands the application range oftraditional videometrics, and enhances the engineering practicality in the aspect ofmacroscopic measurement of videometrics, and has a wide and important applicationalprospect.