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31 January 2020 Where to drive: free space detection with one fisheye camera
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Proceedings Volume 11433, Twelfth International Conference on Machine Vision (ICMV 2019); 114332V (2020) https://doi.org/10.1117/12.2556380
Event: Twelfth International Conference on Machine Vision, 2019, Amsterdam, Netherlands
Abstract
The development in the field of autonomous driving goes hand in hand with ever new developments in the field of image processing and machine learning methods. In order to fully exploit the advantages of deep learning, it is necessary to have sufficient labeled training data available. This is especially not the case for omnidirectional fisheye cameras. As a solution, we propose in this paper to use synthetic training data based on Unity3D. A five-pass algorithm is used to create a virtual fisheye camera. This synthetic training data is evaluated for the application of free space detection for different deep learning network architectures. The results indicate that synthetic fisheye images can be used in deep learning context.
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Tobias Scheck, Adarsh Mallandur, Christian Wiede, and Gangolf Hirtz "Where to drive: free space detection with one fisheye camera", Proc. SPIE 11433, Twelfth International Conference on Machine Vision (ICMV 2019), 114332V (31 January 2020); https://doi.org/10.1117/12.2556380
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