改进DLT算法，更快更准地解决透视n点问题。
Optimal DLT-based Solutions for the Perspective-n-Point
- 用解析加权法优化线性方程组，计算量几乎不变
- 性能和速度优于EPnP、CPnP等主流方法
- 非迭代解接近最优解，适合实时应用
我们提出一种改进的归一化直接线性变换（DLT）算法，用于求解透视n点（PnP）问题，其表现显著优于传统DLT。该改进通过解析方式对线性系统中的不同测量值进行加权，计算开销几乎不增加。与EPnP、CPnP、RPnP和OPnP等流行方法相比，新方法在性能和运行时间上均有明显提升。我们的非迭代最优DLT（oDLT）解决方案逼近通过高斯-牛顿优化获得的真实最优解，但计算成本仅为后者的几分之一。oDLT实现及实验代码已开源。
原文摘要 · Abstract (English)
We propose a modified normalized direct linear transform (DLT) algorithm for solving the perspective-n-point (PnP) problem with much better behavior than the conventional DLT. The modification consists of analytically weighting the different measurements in the linear system with a negligible increase in computational load. Our approach exhibits clear improvements -- in both performance and runtime -- when compared to popular methods such as EPnP, CPnP, RPnP, and OPnP. Our new non-iterative solution approaches that of the true optimal found via Gauss-Newton optimization, but at a fraction of the computational cost. Our optimal DLT (oDLT) implementation, as well as the experiments, are released in open source.
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