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3D coordinate transform model of optical images fusing vector distance information

机译:融合矢量距离信息的光学图像3D坐标变换模型

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For reducing the error of affine transform while matching the three-dimensional targets in optical images, the model of optical images matching was extended to three dimension using distance information of high characteristics in optical images (vector distance information), the three-dimensional (3D) coordinate transform was proposed. Theoretical analysis shows that when the optical imaging model was simplified to pinhole imaging model, the error of 3D coordinate transform didn't exist, while avoiding the nonlinear problem. The amount of calculation of 3D coordinate transform was analyzed using least squares estimation and RANSAC estimation as examples; the amount of calculation of 3D coordinate transform is only four times of affine transform, twice when using RANSAC estimates. The simulation analysis of matching tracking algorithm based on SIFT feature points using 3D coordinate transform was taken by the visual simulation software VegaPrime and MATLAB, and the advantages of 3D coordinate transform has been verified.
机译:为了在匹配光学图像中的三维目标时减少仿射变换的误差,使用光学图像中具有高特征的距离信息(矢量距离信息),三维(3D)将光学图像匹配模型扩展到三维。 )提出了坐标变换。理论分析表明,将光学成像模型简化为针孔成像模型时,不存在3D坐标变换误差,避免了非线性问题。以最小二乘估计和RANSAC估计为例分析了3D坐标变换的计算量。 3D坐标变换的计算量仅为仿射变换的四倍,而使用RANSAC估算时则为两倍。通过可视化仿真软件VegaPrime和MATLAB对基于SIFT特征点的3D坐标变换的匹配跟踪算法进行了仿真分析,验证了3D坐标变换的优点。

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