融合全景影像和车载点云的交通标志信息提取

Traffic Sign Information Extraction Based on Panoramic Images and MLS Point Clouds

交通标志是城市道路交通设施的重要组成部分,对行人行车安全起着重要作用。本文融合激光点云和全景影像提出一种基于图像纹理、颜色、语义信息辅助的交通标志提取方法。本文方法在多个城市场景进行了定性与定量分析,实验结果表明本文方法能适应城市不同场景,点云标志平均提取正确率达97.9%,提取结果可以为城市交通标志规划验收、监测维护以及自动驾驶等领域提供科学辅助方案。

Traffic sign is a significant part of road traffic facilities in city scene and plays an important role in pedestrian and traffic safety. In this paper, by fusing laser point clouds and panoramic images, we propose a method to extract traffic signs in point clouds by using texture, color and semantics of images. The method in this paper has been analyzed qualitatively and quantitatively in several urban scenes. The experimental results show that the method in this paper can adapt to different urban scenes, and the average extraction accuracy of signs reaches 97.9%. The extraction results can provide a scientific auxiliary scheme for city traffic sign planning acceptance, monitoring and maintenance, as well as the fields of automatic driving.