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文章基本信息

  • 标题:Fast road obstacle detection method based on maximally stable extremal regions
  • 作者:Xu Yi ; Gao Song ; Tan Derong
  • 期刊名称:International Journal of Advanced Robotic Systems
  • 印刷版ISSN:1729-8806
  • 电子版ISSN:1729-8814
  • 出版年度:2018
  • 卷号:15
  • 期号:1
  • DOI:10.1177/1729881418759118
  • 语种:English
  • 出版社:SAGE Publications
  • 摘要:Road obstacle detection is an important component of the advanced driver assistance system, and to improve the speed and accuracy of road obstacle detection method is a vital task. In this article, fast image region-matching method based on the maximally stable extremal regions method is proposed to improve the speed of image matching. The theoretical feasibility of detection method combining monocular camera with inertial measurement unit (IMU) is clarified. The fast road obstacle detection method based on maximally stable extremal regions combining fast image region-matching method based on maximally stable extremal regions and the vision-IMU-based obstacle detection method is proposed to bypass obstacle classification and to reduce time and space complexity for road environment perception. The AdaBoost cascade detector, the speeded-up robust features-based obstacle detection method, and the proposed method are used to detect obstacles in outdoor contrast tests. Test results show that the proposed method has higher accuracy, and the reason of high accuracy is analyzed. The processing time of AdaBoost cascade detector, speeded-up robust features-based obstacle detection method, and proposed method are compared, and the results show that the proposed method has faster processing speed, and the reason of faster processing speed is analyzed.
  • 关键词:Road obstacle detection; MSER; pinhole camera model; IMU
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