تقرير
Surround-View Fisheye Optics in Computer Vision and Simulation: Survey and Challenges
العنوان: | Surround-View Fisheye Optics in Computer Vision and Simulation: Survey and Challenges |
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المؤلفون: | Jakab, Daniel, Deegan, Brian Michael, Sharma, Sushil, Grua, Eoin Martino, Horgan, Jonathan, Ward, Enda, Van De Ven, Pepijn, Scanlan, Anthony, Eising, Ciarán |
المصدر: | IEEE Transactions on Intelligent Transportation Systems, 2024 |
سنة النشر: | 2024 |
المجموعة: | Computer Science |
مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition, Electrical Engineering and Systems Science - Image and Video Processing |
الوصف: | In this paper, we provide a survey on automotive surround-view fisheye optics, with an emphasis on the impact of optical artifacts on computer vision tasks in autonomous driving and ADAS. The automotive industry has advanced in applying state-of-the-art computer vision to enhance road safety and provide automated driving functionality. When using camera systems on vehicles, there is a particular need for a wide field of view to capture the entire vehicle's surroundings, in areas such as low-speed maneuvering, automated parking, and cocoon sensing. However, one crucial challenge in surround-view cameras is the strong optical aberrations of the fisheye camera, which is an area that has received little attention in the literature. Additionally, a comprehensive dataset is needed for testing safety-critical scenarios in vehicle automation. The industry has turned to simulation as a cost-effective strategy for creating synthetic datasets with surround-view camera imagery. We examine different simulation methods (such as model-driven and data-driven simulations) and discuss the simulators' ability (or lack thereof) to model real-world optical performance. Overall, this paper highlights the optical aberrations in automotive fisheye datasets, and the limitations of optical reality in simulated fisheye datasets, with a focus on computer vision in surround-view optical systems. Comment: 23 pages, 19 figures, 2 tables |
نوع الوثيقة: | Working Paper |
DOI: | 10.1109/TITS.2024.3368136 |
URL الوصول: | http://arxiv.org/abs/2402.12041 |
رقم الأكسشن: | edsarx.2402.12041 |
قاعدة البيانات: | arXiv |
DOI: | 10.1109/TITS.2024.3368136 |
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