一种高精度的相机姿态线性确定方法

Sen Yang
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引用次数: 0

摘要

本文研究了一种高精度的相机姿态线性确定方法。其核心思想是用加权代数误差代替经典线性方法中的代数误差作为几何误差的近似值。该方法提供了一种线性解,其精度接近最大似然估计,但比最大似然估计效率更高。在EPnP算法[15]的基础上,利用加权线性技术得到了加权EPnP (WEPnP)算法。在模拟数据和真实图像上的实验表明,WEPnP算法明显优于EPnP算法,并且在深度比较小的情况下,它甚至优于Lu的非线性算法[13]。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A high-precision linear method for camera pose determination
This paper concerns a high-precision linear method for camera pose determination. The key idea is to replace the algebraic error in the classical linear method with the weighted algebraic error as an approximation of the geometric error. The proposed method provides a linear solution with accuracy closed to that of maximum likelihood (ML) estimation, but more efficient than ML estimation. Based on the EPnP algorithm [15], we obtain the weighted EPnP (WEPnP) algorithm by using the weighted linear technique. Experiments on simulative data and real images show that the WEPnP algorithm significantly outperforms the EPnP algorithm, what's more, it even outperforms the Lu's nonlinear algorithm [13] in the case of small depth ratio.
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