Abstract
Road detection is one of the key issues for intelligent vehicles and advanced driver assistance systems (ADAS). In this paper, we present a stereovision-based approach for estimating the boundary between the drivable road region and the non-road region. It is based on a formulation of stereo with the ground-plane-induced homography in a hidden Markov model (HMM). Under this formulation, we employ the Viterbi algorithm and propose a sophisticated measure of the probability of the state sequence to find the most likely road/non-road boundary. Experimental results on a wide variety of typical but challenging real road scenes have substantiated the effectiveness as well as robustness of the proposed approach.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
