NDLI: Robust road boundary estimation for intelligent vehicles in challenging scenarios based on a semantic graph

Content Provider	IEEE Xplore Digital Library
Author	Chunzhao Guo Yamabe, T. Mita, S.
Copyright Year	2012
Description	Author affiliation: Toyota Technological Institute, Nagoya, Aichi 468-8511 Japan (Chunzhao Guo; Yamabe, T.; Mita, S.)
Abstract	This paper presents a stereovision-based detection and tracking approach of the drivable road boundary, designed for navigating an intelligent vehicle through challenging traffic scenarios, and increment road safety in such scenarios with advanced driver assistance systems (ADAS). It is based on a formulation of stereo with homography associated with a semantic graph constructed from the traffic scene. Under this formulation, we employ the Viterbi algorithm and propose a sophisticated measure of the probability of the state sequence in the semantic graph to find the most likely boundary between the road and non-road regions. The results are then refined by a post-processing step with the RANdom Sample Consensus (RANSAC) algorithm to obtain the locations and curvatures of the lateral road boundaries. 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.
Starting Page	37
Ending Page	44
File Size	819162
Page Count	8
File Format	PDF
ISBN	9781467321198
ISSN	19310587
e-ISBN	9781467321181
DOI	10.1109/IVS.2012.6232149
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-03
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Roads Robustness Semantics Image segmentation Vehicles Estimation Geometry
Content Type	Text
Resource Type	Article

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