Journal
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
Volume 48, Issue 5, Pages 755-766Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSMC.2016.2616490
Keywords
Autonomous vehicle; inverse perspective mapping (IPM); vanishing point; Weber's law
Funding
- National Natural Science Foundation of China [61472053, 91420102, 61190122]
- National Key Basic Research Program of China (973 Program) [2013CB329103, 2013CB329100]
- Research Grants of University of Macau [MYRG2015-00049-FST, MYRG2015-00050-FST, 008-2014-AMJ]
- Natural Science Foundation Project of CQ CSTC [cstc2012jjA40017]
- China Post-Doctoral Science Foundation [2014M550456]
- Chongqing Post-Doctoral Special Funding Project [Xm2014087]
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Fast and accurate visual scene understanding in autonomous vehicles is necessary but still very challenging. An autonomous vehicle must be taught to read the road like a human driver for better controlling the vehicle, so it is important to efficiently detect the road area and road markings. In this paper, we mainly focus on the vanishing point detection and its application in inverse perspective mapping (IPM) for road marking understanding. We first propose a fast and accurate vanishing point detection method for various types of roads, by adopting and improving Weber local descriptor to obtain salient representative texture and orientation information of the road area, and then voting for the dominant vanishing point with a simple line-voting scheme. Experimental results demonstrate that the proposed vanishing point detection approach gains a better performance than some state-of-the-art methods in terms of accuracy and computation time. Furthermore, we introduce the detected vanishing point into the IPM algorithm in the structured road environment, since some important calibration parameters can be automatically calculated by the vanishing point, especially on the rough road. Experiments also show that our proposed vanishing point-based IPM method is adaptive and accurate, which is conducive to the subsequent road marking detection and recognition.
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