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Overview and Empirical Analysis of ISP Parameter Tuning for Visual Perception in Autonomous Driving

Valeo Vision Systems, Dunmore Road, Tuam, Co. Galway H54 Y276, Ireland
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J. Imaging 2019, 5(10), 78; https://doi.org/10.3390/jimaging5100078
Received: 28 June 2019 / Revised: 8 September 2019 / Accepted: 16 September 2019 / Published: 24 September 2019
Image quality is a well understood concept for human viewing applications, particularly in the multimedia space, but increasingly in an automotive context as well. The rise in prominence of autonomous driving and computer vision brings to the fore research in the area of the impact of image quality in camera perception for tasks such as recognition, localization and reconstruction. While the definition of “image quality” for computer vision may be ill-defined, what is clear is that the configuration of the image signal processing pipeline is the key factor in controlling the image quality for computer vision. This paper is partly review and partly positional with demonstration of several preliminary results promising for future research. As such, we give an overview of what is an View Full-Text
Keywords: image signal processing; computer vision; autonomous driving; localization; reconstruction; recognition image signal processing; computer vision; autonomous driving; localization; reconstruction; recognition
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Yahiaoui, L.; Horgan, J.; Deegan, B.; Yogamani, S.; Hughes, C.; Denny, P. Overview and Empirical Analysis of ISP Parameter Tuning for Visual Perception in Autonomous Driving. J. Imaging 2019, 5, 78.

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