基于双目视觉的三维姿态求解算法研究

Jiaxin Wu, Han Ai, H. Zhang, Jianzhong Cao
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引用次数: 0

摘要

由于空间光照环境复杂,航天器表面涂层材料参差不齐,且具有较强的反射特性,导致在阳光照射下图像出现极亮或极暗的复杂问题,难以提取稳定特征。此外,对于实际测量系统而言,图像特征处理和图像匹配的数据量较大,使得关键算法的速度无法满足应用的实时性。因此,针对上述问题,本文提出了一套基于双目视觉的三维测量算法,主要包括摄像机标定、图像校正、立体匹配和位姿求解四个部分。我们使用传统的图像处理算法对卫星图像进行处理,使用M软件对摄像机进行标定,并对标定结果进行进一步优化和校正,由于实时性的要求,在ORB算法的基础上,使用Fast算法进行特征点提取和Brief描述符计算,并融合极性约束进行特征匹配。提高算法的鲁棒性和实时性,通过旋转角度进行姿态求解。实验表明,该算法能够快速、准确地实现三维姿态测量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on the algorithm of 3D pose solving based on binocular vision
Due to the complex lighting environment in space, the surface coating material of the spacecraft is uneven and has strong reflection characteristics, resulting in the complex problem of extremely bright or extremely dark in the image under sunlight, and it is difficult to extract stable features. In addition, for the actual measurement system, the amount of data for image feature processing and image matching is large, which makes the speed of the key algorithm unable to meet the real-time nature of the application. Therefore, based on the above problems, this paper proposes a set of threedimensional measurement algorithms based on binocular vision, mainly has four parts, camera calibration, Image correction, stereo matching and pose solving. We use traditional image processing algorithm for satellite image, using M software for camera calibration, and the calibration results are further optimized and corrected, due to the requirements of real-time, based on ORB algorithm, the use of Fast algorithm for feature point extraction and descriptor calculation by Brief, and the polar constraint is fused for feature matching. Improve the robustness and real-time performance of the algorithm, and perform pose solving by rotating angle. Experiments show that the algorithm can quickly and accurately achieve three-dimensional pose measurement.
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