Plan3D: Viewpoint and trajectory optimization for aerial multi-view stereo reconstruction

Benjamin Hepp, Matthias Niebner, Otmar Hilliges

Research output: Contribution to journalArticlepeer-review

88 Scopus citations


We introduce a new method that efficiently computes a set of viewpoints and trajectories for high-quality 3D reconstructions in outdoor environments. Our goal is to automatically explore an unknown area and obtain a complete 3D scan of a region of interest (e.g., a large building). Images from a commodity RGB camera, mounted on an autonomously navigated quadcopter, are fed into a multi-view stereo reconstruction pipeline that produces high-quality results but is computationally expensive. In this setting, the scanning result is constrained by the restricted flight time of quad-copters. To this end, we introduce a novel optimization strategy that respects these constraints by maximizing the information gain from sparsely sampled viewpoints while limiting the total travel distance of the quadcopter. At the core of our method lies a hierarchical volumetric representation that allows the algorithm to distinguish between unknown, free, and occupied space. Furthermore, our information gain-based formulation leverages this representation to handle occlusions in an efficient manner. In addition to the surface geometry, we utilize free-space information to avoid obstacles and determine collision-free flight paths. Our tool can be used to specify the region of interest and to plan trajectories. We demonstrate our method by obtaining a number of compelling 3D reconstructions, and we provide a thorough quantitative evaluation showing improvement over previous state-of-the-art and regular patterns.

Original languageEnglish
Article numbera4
JournalACM Transactions on Graphics
Issue number1
StatePublished - Dec 2018


  • 3D reconstruction
  • Submodular optimization
  • Viewpoint planning


Dive into the research topics of 'Plan3D: Viewpoint and trajectory optimization for aerial multi-view stereo reconstruction'. Together they form a unique fingerprint.

Cite this