The process of planning views to observe a scene is known as the Next Best View (NBV) problem. Approaches often aim to obtain high-quality scene observations while reducing the number of views, travel distance and computational cost. Considering occlusions and scene coverage can significantly reduce the number of views and travel distance required to obtain an observation. Structured representations (e.g., a voxel grid or surface mesh) typically use raycasting to evaluate the visibility of represented structures but this is often computationally expensive. Unstructured representations (e.g., point density) avoid the computational overhead of maintaining and raycasting a structure imposed on the scene but as a result do not proactively predict the success of future measurements. This paper presents proactive solutions for handling occlusions and considering scene coverage with an unstructured representation. Their performance is evaluated by extending the density-based Surface Edge Explorer (SEE). Experiments show that these techniques allow an unstructured representation to observe scenes with fewer views and shorter distances while retaining high observation quality and low computational cost.

中文翻译：

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主动估计遮挡和场景覆盖，以在非结构化表示中规划下一个最佳视图

规划视图以观察场景的过程称为下一个最佳视图 (NBV) 问题。方法通常旨在获得高质量的场景观察，同时减少视图数量、行进距离和计算成本。考虑遮挡和场景覆盖可以显着减少获得观察所需的视图数量和行进距离。结构化表示（例如，体素网格或表面网格）通常使用光线投射来评估表示结构的可见性，但这通常在计算上是昂贵的。非结构化表示（例如，点密度）避免了维护和光线投射强加在场景上的结构的计算开销，但因此不会主动预测未来测量的成功。本文提出了处理遮挡和考虑使用非结构化表示的场景覆盖的主动解决方案。它们的性能是通过扩展基于密度的 Surface Edge Explorer (SEE) 来评估的。实验表明，这些技术允许非结构化表示以更少的视图和更短的距离观察场景，同时保持高观察质量和低计算成本。