Vehicle localization in urban environments using feature maps and aerial images
Vehicle localization in urban environments using feature maps and aerial images
复制标题
使用特征图和航空图像在城市环境中进行车辆定位
DOI：
--
复制
发表时间：
2011
期刊：
影响因子：
--
通讯作者：
G. Wanielik
中科院分区：
文献类型：
--
作者：
N. Mattern;G. Wanielik
本文提出了基于车辆运动数据、低成本GNSS接收器、灰度相机和不同数字地图数据的贝叶斯车辆定位算法的两种变体。该算法的关键思想不是从相机图像中提取点或线等特征进行贝叶斯更新，而是对整个图像进行预测。第一种变型基于数字地图的明确地标信息进行图像预测，而第二种变型直接基于航空图像预测相机图像。在此过程中，不需要从航空图像到特征地图的转换步骤。最后，本文给出了基于大量试驾数据和高精度参考数据的两种方法的结果。
This paper presents two variants of a Bayesian algorithm for vehicle localization which use vehicle motion data, a low-cost GNSS receiver, a gray scale camera, and different digital map data. The key idea of the algorithm is not to extract features like points or lines from the camera image for the Bayes update, but to predict entire images. While the first variant performs this image prediction based on explicit landmark information of a digital map, the second variant predicts camera images directly based on aerial images. In doing so, no conversion step from aerial images to feature maps is necessary. Finally, the paper presents results for both approaches based on extensive test drive data with highly accurate reference data.