Fusing ladar and color image for detection grass off-road scenario

Li Da-xue, Wu Tao, Dai Bin
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引用次数: 8

Abstract

It is necessary to extend the intelligent vehicle to navigate from structured environment to rough terrain, which is a great challenge for environment modeling. Ladar and camera are the most widely used sensors, but each of them has shortcoming. In this paper, SVM method is used to fuse the information from ladar and color camera. After registration, ladar point is represented by its position and neighbored pixels in the image. The height of the object as well as the H and S components of the color of the pixels are selected to represent the terrain. Grass and non-grass terrain are recognized based on the features. Experiment shows this method is simple and efficiency.
融合雷达和彩色图像检测草地越野场景
将智能车辆的导航能力从结构化环境扩展到崎岖地形是必要的,这对环境建模是一个巨大的挑战。雷达和相机是应用最广泛的传感器,但它们都有各自的缺点。本文采用支持向量机方法对雷达和彩色摄像机信息进行融合。配准后,雷达点由其在图像中的位置和相邻像素表示。物体的高度以及像素颜色的H和S分量被选择来表示地形。根据地形特征对草地和非草地地形进行识别。实验表明,该方法简单有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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