TY - JOUR A1 - Molloy, Dara A1 - Müller, Patrick A1 - Deegan, Brian A1 - Mullins, Darragh A1 - Horgan, Jonathan A1 - Ward, Enda A1 - Jones, Edward A1 - Braun, Alexander A1 - Glavin, Martin T1 - Analysis of the Impact of Lens Blur on Safety-Critical Automotive Object Detection JF - IEEE Access N2 - Camera-based object detection is widely used in safety-critical applications such as advanced driver assistance systems (ADAS) and autonomous vehicle research. Road infrastructure has been designed for human vision, so computer vision, with RGB cameras, is a vital source of semantic information from the environment. Sensors, such as LIDAR and RADAR, are also often utilized for these applications; however, cameras provide a higher spatial resolution and color information. The spatial frequency response (SFR), or sharpness of a camera, utilized in object detection systems must be sufficient to allow a detection algorithm to localize objects in the environment over its lifetime reliably. This study explores the relationship between object detection performance and SFR. Six state-of-the-art object detection models are evaluated with varying levels of lens defocus. A novel raw image dataset is created and utilized, containing pedestrians and cars over a range of distances up to 100-m from the sensor. Object detection performance for each defocused dataset is analyzed over a range of distances to determine the minimum SFR necessary in each case. Results show that the relationship between object detection performance and lens blur is much more complex than previous studies have found due to lens field curvature, chromatic aberration, and astigmatisms. We have found that smaller objects are disproportionately impacted by lens blur, and different object detection models have differing levels of robustness to lens blur KW - DOAJ KW - Object detection KW - intelligent transportation system KW - autonomous vehicles KW - ADAS KW - lens blur Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:due62-opus-42999 SN - 2169-3536 VL - 12 SP - 3554 EP - 3569 PB - IEEE ER - TY - JOUR A1 - Jakab, Daniel A1 - Braun, Alexander A1 - Agnew, Cathaoir A1 - Mohandas, Reenu A1 - Deegan, Brian Michael A1 - Molloy, Dara A1 - Ward, Enda A1 - Scanlan, Anthony A1 - Eising, Ciarán T1 - SS-SFR: synthetic scenes spatial frequency response on Virtual KITTI and degraded automotive simulations for object detection JF - IET Conference Proceedings Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:due62-opus-50080 SN - 2732-4494 VL - 2024 IS - 10 SP - 110 EP - 117 PB - Institution of Engineering and Technology (IET) ER - TY - JOUR A1 - Jakab, Daniel A1 - Vázquez, Joel Herrera A1 - Barthel, Julian A1 - Honsbrok, Jan A1 - Deegan, Brian A1 - Mohandas, Reenu A1 - Brophy, Tim A1 - Scanlan, Anthony A1 - Ward, Enda A1 - Collins, Fiachra A1 - Eising, Ciarán A1 - Braun, Alexander T1 - SOLAS 1.1: Automotive Optical Simulation in Computer Vision (Early Access) JF - IEEE Open Journal of Vehicular Technology KW - Optical imaging KW - Optical distortion KW - Cameras KW - Lenses KW - Automotive engineering KW - Adaptive optics KW - Object detection KW - Computer vision KW - Optical sensors KW - Production Y1 - 2025 U6 - https://doi.org/10.1109/OJVT.2025.3640419 SN - 2644-1330 N1 - The supplemental material contains material to support the article. DOI:10.1109/OJVT.2025.3640419/mm1 SP - 1 EP - 16 PB - Institute of Electrical and Electronics Engineers ER -