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| Type | Conference or Workshop Paper |
| Scope | Discipline-based scholarship |
| Published in Proceedings | Yes |
| Title | Active Exposure Control for Robust Visual Odometry in HDR Environments |
| Organization Unit | |
| Authors |
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| Presentation Type | paper |
| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| ISSN | 1050-4729 |
| Page Range | 1 - 9 |
| Event Title | IEEE International Conference on Robotics and Automation (ICRA), 2017. |
| Event Type | conference |
| Event Location | Singapore |
| Event Start Date | May 29 - 2017 |
| Event End Date | June 2 - 2017 |
| Series Name | IEEE International Conference on Robotics and Automation. Proceedings |
| Place of Publication | IEEE International Conference on Robotics and Automation (ICRA), 2017. |
| Publisher | Institute of Electrical and Electronics Engineers |
| Abstract Text | In this paper, 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 both the built-in auto-exposure function of the camera and a fixed exposure time. To validate the benefit of our approach, we test different state-of-the-art visual odometry pipelines (namely, ORB-SLAM2, DSO, and SVO 2.0) and demonstrate significant improved performance using our exposure control method in very challenging HDR environments. Datasets and code will be released soon! |
| Zusammenfassung | In this paper, 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 both the built-in auto-exposure function of the camera and a fixed exposure time. To validate the benefit of our approach, we test different state-of-the-art visual odometry pipelines (namely, ORB-SLAM2, DSO, and SVO 2.0) and demonstrate significant improved performance using our exposure control method in very challenging HDR environments. Datasets and code will be released soon! |
| Free access at | Official URL |
| Official URL | http://rpg.ifi.uzh.ch/docs/ICRA17_Zhang.pdf |
| Digital Object Identifier | 10.1109/ICRA.2017.7989449 |
| PubMed ID | http://rpg.ifi.uzh.ch/docs/ICRA17_Zhang.pdf |
| Other Identification Number | merlin-id:14830 |
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