航空影像车辆状态估计的精度表征
Accuracy Characterization of the Vehicle State Estimation from Aerial Imagery
摘要：
由于其获取空中图像的能力，配备摄像机的无人机（UAV）是获取交通信息的非常经济有效的工具。然而，没有足够的注意力已经给予这些系统的准确性验证。本文分析了最重要的误差来源。这包括三个关键组成部分。首先，通过统计滤波的车辆状态估计。第二，量化最重要的误差来源。第三，与最先进的参考传感器相比的估计状态的基准。这项工作提出了尽量减少最相关来源的错误的方法。由于这些误差减少，配备摄像机的无人机是非常有吸引力的交通数据采集工具。测试数据和源代码是公开的。
英文摘要：
Due to their capability of acquiring aerial imagery, camera-equipped Unmanned Aerial Vehicles (UAVs) are very cost-effective tools for acquiring traffic information. However, not enough attention has been given to the validation of the accuracy of these systems. In this paper, an analysis of the most significant sources of error is done. This includes three key components. First, a vehicle state estimation by means of statistical filtering. Second, a quantification of the most significant sources of error. Third, a benchmark of the estimated state compared with state-of-the-art reference sensors. This work presents ways to minimize the errors of the most relevant sources. With these error reductions, camera-equipped UAVs are very attractive tools for traffic data acquisition. The test data and the source code are made publicly available.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
