Back to articles
Articles
Volume: 33 | Article ID: art00007
Image
End-to-End Imaging System Optimization for Computer Vision in Driving Automation
  DOI :  10.2352/ISSN.2470-1173.2021.17.AVM-173  Published OnlineJanuary 2021
Abstract

Full driving automation imposes to date unmet performance requirements on camera and computer vision systems, in order to replace the visual system of a human driver in any conditions. So far, the individual components of an automotive camera hav mostly been optimized independently, or without taking into account the effect on the computer vision applications. We propose an end-to-end optimization of the imaging system in software, from generation of radiometric input data over physically based camera component models to the output of a computer vision system. Specifically, we present an optimization framework which extends the ISETCam and ISET3d toolboxes to create synthetic spectral data of high dynamic range, and which models a stateof-the-art automotive camera in more detail. It includes a stateof-the-art object detection system as benchmark application. We highlight in which way the framework approximates the physical image formation process. As a result, we provide guidelines for optimization experiments involving modification of the model parameters, and show how these apply to a first experiment on high dynamic range imaging.

Subject Areas :
Views 38
Downloads 10
 articleview.views 38
 articleview.downloads 10
  Cite this article 

Korbinian Weikl, Damien Schroeder, Daniel Blau, Zhenyi Liu, Walter Stechele, "End-to-End Imaging System Optimization for Computer Vision in Driving Automationin Proc. IS&T Int’l. Symp. on Electronic Imaging: Autonomous Vehicles and Machines,  2021,  pp 173-1 - 173-7,  https://doi.org/10.2352/ISSN.2470-1173.2021.17.AVM-173

 Copy citation
  Copyright statement 
Copyright © Society for Imaging Science and Technology 2021
72010604
Electronic Imaging
2470-1173
Society for Imaging Science and Technology
IS&T 7003 Kilworth Lane, Springfield, VA 22151 USA