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Illumination invariance for driving scene optical flow using comparagram preselection
Goethe Universität Frankfurt, Visual Sensorics and Information Processing Lab, Frankfurt, Germany.
Daimler AG, Sindelfingen, Germany.
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
2012 (English)In: IEEE Intelligent Vehicles Symposium (IV), Proceedings, Institute of Electrical and Electronics Engineers (IEEE) , 2012, 742-747 p.Conference paper (Other academic)
Abstract [en]

In the recent years, advanced video sensors have become common in driver assistance, coping with the highly dynamic lighting conditions by nonlinear exposure adjustments. However, many computer vision algorithms are still highly sensitive to the resulting sudden brightness changes. We present a method that is able to estimate the relative intensity transfer function (RITF) between images in a sequence even for moving cameras. The according compensation of the input images can improve the performance of further vision tasks significantly, here demonstrated by results from optical flow. Our method identifies corresponding intensity values from areas in the images where no apparent motion is present. The RITF is then estimated from that data and regularized based on its curvature. Finally, built-in tests reliably flag image pairs with adverse conditions where no compensation could be performed. © 2012 IEEE.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2012. 742-747 p.
, IEEE Intelligent Vehicles Symposium, Proceedings, ISSN 1931-0587 ; 4
Keyword [en]
computer vision, driver information systems, image sensors, image sequences, lighting
National Category
Engineering and Technology
URN: urn:nbn:se:liu:diva-101143DOI: 10.1109/IVS.2012.6232281ISI: 000309167700121ISBN: 978-1-4673-2119-8ISBN: 978-1-4673-2118-1OAI: diva2:665610
2012 Intelligent Vehicles Symposium Alcalá de Henares, Spain, June 3-7, 2012
Available from: 2013-11-20 Created: 2013-11-19 Last updated: 2014-03-06Bibliographically approved

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Mester, Rudolf
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Computer VisionThe Institute of Technology
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