Details

Autor(en) / Beteiligte

• Zichao Zhang
• Forster, Christian
• Scaramuzza, Davide

Titel

Active exposure control for robust visual odometry in HDR environments

Ist Teil von

• 2017 IEEE International Conference on Robotics and Automation (ICRA), 2017, p.3894-3901

Ort / Verlag

IEEE

Erscheinungsjahr

2017

Quelle

IEEE Electronic Library (IEL)

Beschreibungen/Notizen

• We propose an active exposure control method to improve the robustness of visual odometry in HDR (high dynamic range) environments. Our method evaluates the proper exposure time by maximizing a robust gradient-based image quality metric. The optimization is achieved by exploiting the photometric response function of the camera. Our exposure control method is evaluated in different real world environments and outperforms the built-in auto-exposure function of the camera. To validate the benefit of our approach, we adapt a state-of-the-art visual odometry pipeline (SVO) to work with varying exposure time and demonstrate improved performance using our exposure control method in challenging HDR environments.