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首页> 外文期刊>Pattern Recognition: The Journal of the Pattern Recognition Society >Real-time geometric fitting and pose estimation for surface of revolution
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Real-time geometric fitting and pose estimation for surface of revolution

机译:革命表面的实时几何拟合和姿态估计

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摘要

This paper presents a novel ellipse fitting method to simultaneously estimate the Euclidean pose and structure of a surface of revolution (SOR) by minimizing the geometric reprojection error of the visible cross sections in image space. This geometric error function and its Jacobian matrix are explicitly derived to enable Levenberg-Marquardt (LM) optimization. With the obtained pose and structure, the Euclidean shape of a SOR can be reconstructed by generating the ellipse tangency to the apparent contour of the SOR. Given the real size of several visible cross sections, this approach can be extended to perform a real-time 3D tracking of the SOR. Additionally, this technique can be also generalized to fitting for imaged parallel circles. Sufficient experiments validate the accuracy and the real-time performance of the proposed method. (C) 2018 Elsevier Ltd. All rights reserved.
机译:本文通过最小化图像空间中可见横截面的几何刻录误差,同时估计旋转(SOR)表面的欧几里德姿势和结构的新颖椭圆拟合方法。 该几何误差函数及其雅可族矩阵被明确导出,以使Levenberg-Marquardt(LM)优化。 利用所获得的姿势和结构,可以通过产生椭圆形切线对SOR的表观轮廓来重建SOR的欧几里德形状。 鉴于几个可见横截面的真实尺寸,可以扩展这种方法以执行SOR的实时3D跟踪。 另外,该技术也可以概括地拟合成像平行圆。 足够的实验验证了所提出的方法的准确性和实时性能。 (c)2018年elestvier有限公司保留所有权利。

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