Multi-view triangulation is an essential step in recovering three-dimensional structure from a set of images. It is a well-studied problem in computer vision with many suboptimal and optimal methods based on different optimality criteria. In this paper, we assess the ability of evolutionary computation (EC) methods in finding highly accurate solutions to this problem. We use an overlaying Luus–Jaakola optimizer to find good parameter configurations and determine appropriate computational budget for the EC methods. Empirical results on synthetic and real data demonstrate the superior performance of EC methods over existing triangulation methods.

中文翻译：

---

关于多视图三角剖分的进化计算技术

多视图三角剖分是从一组图像中恢复三维结构的重要步骤。它是计算机视觉中一个经过充分研究的问题，基于不同的最优性标准，有许多次优和最优的方法。在本文中，我们评估了进化计算（EC）方法寻找此问题的高精度解决方案的能力。我们使用重叠的Luus–Jaakola优化器来找到良好的参数配置，并为EC方法确定适当的计算预算。综合和真实数据的经验结果表明，EC方法优于现有的三角测量方法。