Real time Detection of Lane Markers in Urban Streets

TL;DR

This paper introduces a real-time lane marker detection method for urban streets that uses top view transformation, Gaussian filtering, and RANSAC-based spline fitting to accurately identify lanes at 50 Hz.

Contribution

It presents a novel fast RANSAC algorithm for Bezier spline fitting in lane detection, enabling real-time performance in complex urban environments.

Findings

Detects all lanes in still images under various conditions

Operates at 50 Hz in real-time

Achieves comparable accuracy to previous methods

Abstract

We present a robust and real time approach to lane marker detection in urban streets. It is based on generating a top view of the road, filtering using selective oriented Gaussian filters, using RANSAC line fitting to give initial guesses to a new and fast RANSAC algorithm for fitting Bezier Splines, which is then followed by a post-processing step. Our algorithm can detect all lanes in still images of the street in various conditions, while operating at a rate of 50 Hz and achieving comparable results to previous techniques.