Objective Three-dimensional trajectory measurement is a key technology involved in intelligent monitoring, motion analysis and target tracking, which has been widely used in transportation, military and other fields. In recent years, with the rapid development of computer vision technology, imaging equipment and computers are used to replace human eyes and brains to measure the three-dimensional trajectory of target objects with high accuracy. Monocular vision mostly estimates the depth distance of the target in the three-dimensional coordinate system through the proportion of pixel area changes. When the target object rotates and deforms, the depth estimation results are greatly affected. However, binocular vision based on 3D reconstruction mathematical model and polar constraint has the advantages of reliable calculation results and relatively high measurement accuracy in 3D trajectory measurement of flying objects. In the three-dimensional trajectory measurement based on binocular vision, the high-precision matching of binocular homonymous points is the key to improve the measurement accuracy. Especially in the narrow and long space near distance measurement scene for aeroengine safety monitoring, because the binocular camera shoots the target object from different angles, especially when the included angle of the optical axis of the binocular camera is large, the trajectory measurement accuracy of only centroid positioning matching is not high. In order to solve the above problems, a near distance trajectory measurement system in narrow and long space based on centroid matching optimization is developed. In the three-dimensional trajectory measurement based on binocular vision, the high-precision matching of binocular homonymous points is the key to improve the measurement accuracy. Especially in the narrow and long space near distance measurement scene of aeroengine safety monitoring, because the binocular camera shoots the target object from different angles, especially when the included angle of the optical axis of the binocular camera is large, the trajectory measurement accuracy of only centroid positioning matching is not high. To solve these problems, a trajectory measurement system based on centroid matching and optimization is developed.
Methods First of all, on the basis of only using the centroid method to locate and match the object, the epipolar constraint projection is used to locate the centroid of the binocular. Then, a gray cross correlation method based on distance and method weight is proposed for subpixel matching of binocular centroids. Finally, Kalman filtering is used to correct the 3D reconstructed motion trajectory of the object, in order to improve the measurement accuracy of the trajectory, the three-dimensional trajectory points with large deviation from the ideal trajectory position caused by the unstable centroid position in the extraction of the target centroid are removed from the three-dimensional trajectory. In the laboratory environment, simulate the narrow and long movement space before the bird enters the engine, build a binocular measurement system at the side close position, and carry out the narrow and long trajectory measurement experiment verification.
Results and Discussions According to the measurement experiment results of different texture target objects (Fig.11, Fig.12, Fig.13 and Tab.1), it can be seen that the depth of the target object's imaging texture has a certain impact on the trajectory measurement accuracy of the measurement system in this paper. Because the gray value distribution of the target object with deeper texture is more abundant, the sub-pixel matching based on gray level cross-correlation has better binocular matching effect, so it has higher measurement accuracy. According to the repeatability experiment results (Fig.14), in the full range of 128 mm, the average trajectory length measurement error of the trajectory measurement system in this paper is 13.14 μm for objects with good texture. The measurement accuracy of track length is about 0.01%, and the straightness error of track is small.
Conclusions Compared with only using centroid method for coarse positioning and matching, the trajectory length measurement accuracy and straightness of the measurement system are significantly improved, and the high-precision measurement of flying object trajectory in the narrow and long space near distance measurement scene is realized. Based on the error analysis of the measurement results, in the actual measurement, the imaging clarity of the target object texture should be improved by improving the light source illumination and optimizing the optical path design, so as to improve the measurement accuracy of the target object trajectory. The follow-up work direction is to optimize the texture of the target object through image enhancement, improve the trajectory measurement accuracy of the measurement system for the target object with poor texture, and further study the high-precision extraction method of non-rigid body and rotating target matching points, so that the entire measurement system has better stability for the trajectory measurement of different target objects in different measurement scenes.
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