• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

计算机工程与科学 ›› 2020, Vol. 42 ›› Issue (07): 1234-1243.doi: 10.3969/j.issn.1007-130X.2020.07.012

• 图形与图像 • 上一篇    下一篇

基于单目视觉的车辆下边沿估计和逆透视变换的车距测量

王永森,刘宏哲   

  1. (北京联合大学北京市信息服务工程重点实验室,北京 100101)
  • 收稿日期:2019-12-05 修回日期:2020-02-27 接受日期:2020-07-25 出版日期:2020-07-25 发布日期:2020-07-25
  • 基金资助:
    国家自然科学基金(61871039);北京市属高校高水平教师队伍建设支持计划(IDHT20170511);北京联合大学领军人才项目(BPHR2019AZ01);北京联合大学项目(202011417004,202011417005;WZ10201903);北京联合大学研究生科研创新资助项目

Vehicle distance measurement with vehicle lower edge estimation  and inverse perspective mapping based on monocular vision

WANG Yong-sen,LIU Hong-zhe   

  1. (Beijing Key Laboratory of Information Service Engineering,Beijing Union University,Beijing 100101,China)
  • Received:2019-12-05 Revised:2020-02-27 Accepted:2020-07-25 Online:2020-07-25 Published:2020-07-25

摘要: 前方车辆测距在自动驾驶汽车技术领域中起着至关重要的作用。针对目前基于单目视觉的车辆测距技术忽略了车辆与地面相接的下边沿问题,提出一种基于车辆下边沿估计和逆透视变换的单目视觉测距方法,实现了对前方车辆进行横向和纵向的高精度车距测量。该方法首先通过对车辆关键点估计和几何关系模型完成对车辆下边沿的估计,然后从中计算测距关键点,再利用基于点的逆透视变换测距模型进行距离计算。实验结果表明,与其他基于单目视觉的车辆测距方法相比,该方法提高了测距的精度和稳定性。

关键词: 单目视觉, 车辆测距, 视觉测距, 逆透视变换, 自动驾驶汽车

Abstract: Front vehicle ranging plays a vital role in the field of autonomous vehicle technology. Aiming at the problem that the current vehicle ranging technology based on monocular vision neglects the lower edge of the vehicle connected to the ground, this paper proposes a monocular vision ranging model based on vehicle lower edge estimation and inverse perspective transformation, which realizes high- precision distance measurement of lateral and longitudinal directions of vehicles in front. Firstly, the vehicle's key point estimation and geometric relationship model are used to estimate the lower edge of the vehicle, then the distance measurement key points are calculated, and the point-based inverse perspective transformation distance measurement model is used to calculate the distance. The experimental results show that, compared with other monocular vision vehicle ranging algorithms, this method improves the accuracy and stability of ranging.


Key words: monocular vision, vehicle distance measurement, visual ranging, inverse perspective mapping, autonomous vehicle

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