Conventional vision-based methodologies encounter challenges when measuring the displacement of the internal point of the object. This paper proposes a practical videogrammetric method for measuring the internal point displacements of the suspendome structure node using a pair of high-speed cameras. Firstly, the intrinsic parameters of each camera are calibrated using a precise calibration board, and the extrinsic parameters are calculated by the bundle adjustment and the circular marks that are fixed in the common field of view. Then, the initial 3D position of internal point of suspendome structure node is calculated by the specially designed marks and the high-precision total station. The displacement of the suspendome structure node's internal point is derived by tracking the markers affixed to the surface of the structure node and combined with spatial coordinate transformation. In a suspendome structure disruption experiment, the internal point's measurement accuracy is about the submillimeter when compared to the total station, and the credibility of the measurements is further verified by comparison with numerical simulations.
The issue of displacement measurement of floating wind turbine model when experiencing wind-wave loads is one important assessment indicator of stability, but conventional contact methods hardly to utilize in environment which are complex and have limited accessibility. Consequently, we develop the high-speed videogrammetry technique for displacement measurement from tremendous image sequences data, which possesses advantages of non-contact, high frame rate, three-dimensional dense measurement when compare to traditional approaches. The first, the motion of model in image sequences are acquired with the accurate target recognition and tracking algorithms. The second, the cameras interior and exterior parameters are determined through camera calibration and bundle adjustment respectively. The third, the target spatial position and displacement in X, Y, and Z directions are finally calculated based on videogrammetry theory. The experiment results demonstrate that the spatial position calculated by proposed approach can reach submillimeter accuracy in three directions when compare to high accuracy total station. In addition, the credibility of displacement results is further proved by the frequency consistence between measured and theoretical.
KEYWORDS: Computing systems, Distributed computing, Image processing, Cameras, High speed cameras, Image transmission, 3D image processing, Data processing, Local area networks
In recent years, high-speed videogrammetry has been used to monitor the three-dimension behavior of large vibrating structures. Traditionally, this has been accomplished by transferring image sequences, captured by several cameras, to a central computer after each test has been conducted. Only then have the images been postprocessed and the required kinematic data extracted. This process is slow and inefficient because a large amount of data (image sequences) must be transferred to the host before the data analysis can begin. In order to address this problem, we have developed a novel system that adopts a distributed data processing strategy. The system which combining the processing power built into each of the individual cameras and the processing power of a central computer, uses a wired local area network. the communication between the nodes and the host is achieved using the TCP/IP protocol and a custom application layer. In this way, the processing power of the entire system is more fully utilized and the overall performance of the video processing system is improved. We describe how we have employed two cameras, operating simultaneously, to test the proposed concept. The experimental results from a series of tests showed that the average time required to perform the necessary image processing was reduced 58.7% by using the distributed processing system instead of a traditionally configured system.
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