A Refined-Line-Based Method to Estimate Vanishing Points for Vision-Based Autonomous Vehicles

Helping vehicles estimate vanishing points (VPs) in traffic environments has considerable value the field of autonomous driving. It multiple unaddressed issues such as refining extracted lines and removing spurious VP candidates, which suffers from low accuracy high computational cost a complex environment. To address these two issues, we present this study new model to VPs monocular camera. Lines that belong structured configuration orientation are refined. At point, it is possible through extracting their corresponding candidates optimal estimation. The algorithm requires no prior training better robustness color illumination on base geometric inferences. Through comparing estimated ground truth, percentage pixel errors were evaluated. results proved methodology successful estimating VPs, meeting requirements for vision-based vehicles.