We propose a new method for segmentation-free joint estimation of orthogonal planes, their intersection lines, relationship graph and corners lying at the intersection of three orthogonal planes. Such unified scene exploration under orthogonality allows for multitudes of applications such as semantic plane detection or local and global scan alignment, which in turn can aid robot localization or grasping tasks. Our two-stage pipeline involves a rough yet joint estimation of orthogonal planes followed by a subsequent joint refinement of plane parameters respecting their orthogonality relations. We form a graph of these primitives, paving the way to the extraction of further reliable features: lines and corners. Our experiments demonstrate the validity of our approach in numerous scenarios from wall detection to 6D tracking, both on synthetic and real data.

中文翻译：

---

从平面到角落：无组织 3D 点云中的多用途基元检测

我们提出了一种对正交平面、它们的相交线、关系图和位于三个正交平面相交处的角进行无分割联合估计的新方法。这种在正交性下的统一场景探索允许多种应用，例如语义平面检测或局部和全局扫描对齐，这反过来又可以帮助机器人定位或抓取任务。我们的两阶段管道涉及对正交平面的粗略但联合估计，然后是平面参数的后续联合细化，尊重它们的正交关系。我们形成了这些基元的图形，为提取更可靠的特征铺平了道路：线和角。我们的实验证明了我们的方法在从墙壁检测到 6D 跟踪的众多场景中的有效性，