Robust lane detection and tracking with RANSAC and Kalman filter

Authors:
Amol Borkar;Monson Hayes;Mark T. Smith
Affiliations:
Center for Signal and Image Processing, Georgia Institute of Technology, Atlanta, GA;Center for Signal and Image Processing, Georgia Institute of Technology, Atlanta, GA;Institut för Tillämpad Informationsteknik, Kungliga Tekniska Högskolan, Stockholm, Sweden
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

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Abstract

In a previous paper, a simple approach to lane detection using the Hough transform and iterated matched filters was described [1]. This paper extends this work by incorporating an inverse perspective mapping to create a bird's-eye view of the road, applying random sample consensus to help eliminate outliers due to noise and artifacts in the road, and a Kalman filter to help smooth the output of the lane tracker.