Details

Autor(en) / Beteiligte

• Lin, Bo-Yi
• Huang, Chih-Sheng
• Lin, Jia-Ming
• Liu, Pin-Hsuan
• Lai, Kuan-Ting

Titel

Traffic Object Detection in Virtual Environments

Ist Teil von

• 2023 International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan), 2023, p.245-246

Ort / Verlag

IEEE

Erscheinungsjahr

2023

Quelle

IEEE Xplore

Beschreibungen/Notizen

• As Virtual Reality (VR) technology becomes more advanced, VR can create scenes that closely resemble the real world. Therefore, automotive industry has started to use VR environments as test bed for autonomous driving algorithms. However, to the best of our knowledge, there is no systematic evaluation for the performance of real-world object detectors in VR worlds. To solve this issue, we used Unreal Engine to construct a virtual environment simulating real street view and AirSim plugin to generate bounding box ground truths. We employed the state-of-the-art object detectors YOLOv7 and YOLOv8 to detect common traffic objects. Our experiments can reveal the strengths and weakness of each detector.