Novel Test Bench for End-to-End Validation of Monocular Depth Estimation Under the Influence of Glaring Situations
Ulreich F, Kaup A, Ebert M (2024)
Publication Type: Conference contribution
Publication year: 2024
Publisher: Institute of Electrical and Electronics Engineers Inc.
Pages Range: 2426-2432
Conference Proceedings Title: IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
Event location: Edmonton, AB, CAN
ISBN: 9798331505929
DOI: 10.1109/ITSC58415.2024.10920009
Abstract
The black-box nature of deep learning models employed in automated driving functions requires suitable evaluation tools. Efforts are being made to increase the validity of testing environments for real-world operations. Understanding the impact of the sensor characteristics and degradation on the downstream task of perception is another field of research. We propose a test environment for vision-based autonomous driving functions in which a real camera and a deep learning model can be evaluated jointly. Our approach enables the validation under real-world brightness conditions through projector technology. To demonstrate its applicability, we employed a Vision Transformer to perform monocular depth estimation. Our experimental setup included a challenging scenario involving glare to assess the differences in performance between the testing environments: camera test bench and simulation. We quantified the gap by contrasting image quality metrics of partly-synthetic and pure synthetic data with real-world data contained in the KITTI depth dataset. With our approach, we were able to produce images that are 37 % closer to real-world than synthetic image data. Also, the gap in data variability is 18 % less than with synthetic data. In addition, we found that clipping in glare situations does not necessarily lead to large errors in depth prediction.
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Germany (DE)How to cite
APA:
Ulreich, F., Kaup, A., & Ebert, M. (2024). Novel Test Bench for End-to-End Validation of Monocular Depth Estimation Under the Influence of Glaring Situations. In IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC (pp. 2426-2432). Edmonton, AB, CAN: Institute of Electrical and Electronics Engineers Inc..
MLA:
Ulreich, Fabian, André Kaup, and Martin Ebert. "Novel Test Bench for End-to-End Validation of Monocular Depth Estimation Under the Influence of Glaring Situations." Proceedings of the 27th IEEE International Conference on Intelligent Transportation Systems, ITSC 2024, Edmonton, AB, CAN Institute of Electrical and Electronics Engineers Inc., 2024. 2426-2432.
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