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Towards video processing in vehicles under adverse weather conditions

 
: Grinberg, Michael; Schneider, N.; Pagel, Frank; Manger, Daniel; Willersinn, Dieter

:
Postprint urn:nbn:de:0011-n-2541030 (4.8 MByte PDF)
MD5 Fingerprint: 68dc821aba42ba8924573edfa2c3d0c2
Copyright Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
Erstellt am: 31.3.2015


Smith, D.G. (Ed.) ; Society of Photo-Optical Instrumentation Engineers -SPIE-, Bellingham/Wash.:
Optical Systems Design 2012 : 26.-29.11.2012, Barcelona, Spain
Bellingham, WA: SPIE, 2012 (Proceedings of SPIE 8550)
ISBN: 978-0-8194-9301-9
Paper 855020, 8 S.
Conference "Optical Systems Design" <2012, Barcelona>
Englisch
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IOSB ()
ADAS; adverse weather conditions; rain; spray detection; tracking; image restoration; ICADAC

Abstract
In this contribution we propose methods for vehicle detection and tracking for the Advanced Driver Assistance Systems (ADAS) that work under extremely adverse weather conditions. Most of the state-of-the-art vehicle detection and tracking methods are based either on appearance based vehicle recognition or on extraction and tracking of dedicated image key points. Visibility deterioration due to rain drops and water streaks on the windshield, swirling spray, and fog lead to a drastic performance reduction or even to a complete failure of these approaches. In this contribution we propose several methods for coping with these phenomena. In addition to an extension of the feature-based tracking method, which copes with outliers and temporarily disappearing key points, we present a detection and tracking method based on search for vehicle rear lights and whole rear views in the saturation channel. Utilization of symmetry operators and search space restriction allows to detect and track vehicles even in pouring rain conditions. Furthermore, we present two applications of the above-described methods. Estimation of the strength of spray produced by preceding vehicles allows to draw conclusions about the overall visibility conditions and to adjust the intensity of one's own rear lights. Besides, a restoration of deteriorated image regions becomes possible.

: http://publica.fraunhofer.de/dokumente/N-254103.html