计算机应用 ›› 2014, Vol. 34 ›› Issue (6): 1762-1764.DOI: 10.11772/j.issn.1001-9081.2014.06.1762

• 虚拟现实与数字媒体 • 上一篇    下一篇

基于三目视觉系统的车辆导引方法

王军1,2,柳红岩1   

  1. 1. 苏州科技学院 电子与信息工程学院,江苏 苏州 215000;
    2. 中国科学院大学,北京 100049
  • 收稿日期:2013-12-25 修回日期:2014-02-18 出版日期:2014-06-01 发布日期:2014-07-02
  • 通讯作者: 柳红岩
  • 作者简介:王军(1979-),男,江苏徐州人,副教授,博士,主要研究方向:光电检测;柳红岩(1990-),女,山西晋中人,硕士研究生,主要研究方向:光电信息、数字图像处理
  • 基金资助:

    江苏省青年科学基金资助项目

Vehicle navigation method based on trinocular vision

WANG Jun1,2,LIU Hongyan1   

  1. 1. College of Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou Jiangsu 215000,China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2013-12-25 Revised:2014-02-18 Online:2014-06-01 Published:2014-07-02
  • Contact: LIU Hongyan

摘要:

为使车辆在非结构化地形环境中实现自动导引,提出一种基于三目立体视觉系统的自适应地形分类方法。该地形分类方法利用三目视觉系统采集地形的几何信息与颜色信息, 方法中的几何分类器通过分析采集的数据对地形进行初步分类,而颜色分类器则在几何分类器的基础上对不同地形进行颜色标注。分类过程中,为使车辆能够有效地适应变化的地形环境,需根据分类所得新数据实时更新原有分类数据。该地形分类方法最终把可行驶的地面和不可行驶的任何地形作出分类并用不同颜色标注。从实验结果可看出,该方法可对实验中三目立体视觉系统所拍摄的地形作出准确分类。

Abstract:

A classification method based on trinocular stereovision, which consisted of geometrical classifier and color classifier, was proposed to autonomously guide vehicles on unstructured terrain. In this method, rich 3D data which were taken by stereovision system included range and color information of the surrounding environment. Then the geometrical classifier was used to detect the broad class of ground according to the collected data, and the color classifier was adopted to label ground subclasses with different colors. During the classifying stage, the new classification data needed to be updated continuously to make the vehicle adapt to variable surrounding environment. Two broad categories of terrain what vehicles can drive and can not drive were marked with different colors by using the classification method. The experimental results show that the classification method can make an accurate classification of the terrain taken by trinocular stereovision system.

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