Semantic 3D Models from Real World Scene Recordings for Traffic Accident Simulation

Ludwig Mohr, Martin Öttl, Michael Haberl, Matthias Rüther, Horst Bischof

Publikation: Beitrag in Buch/Bericht/KonferenzbandBeitrag in einem Konferenzband

Abstract

We propose a novel extension to traffic accident simulation by means of semantic 3D environment information allowing for a broader view by incorporating the entire close-by environment. In this course, the effect of Advanced Driver Assistance Systems (ADAS) can be simulated, as well as the visibility of objects from people’s perspectives. We present an enclosed pipeline generating 3D objects, their extents and relative positions as well as their semantic class from a combination of photogrammetric recordings and LiDAR (Light Detection And Ranging) scans. By adjusting the desired level of detail, these objects are suitable for both direct integration into the 3D scene reconstruction for use in the accident simulation software PC-Crash, as well as for fine tuning parameters in traffic flow simulations and for convincing visualization and presentation of simulation results, be it in courts or to policy makers in urban planning.
Originalspracheenglisch
TitelProceedings of 7th Transport Research Arena TRA 2018
PublikationsstatusVeröffentlicht - 16 Apr 2018

Fingerprint

Untersuchen Sie die Forschungsthemen von „Semantic 3D Models from Real World Scene Recordings for Traffic Accident Simulation“. Zusammen bilden sie einen einzigartigen Fingerprint.

Dieses zitieren