Estimating Road Segments Using Kernelized Averaging of GPS Trajectories
Estimating Road Segments Using Kernelized Averaging of GPS Trajectories
复制标题
DOI：
10.3390/app9132736
复制
发表时间：
2019-07-01
影响因子：
2.7
通讯作者：
Marteau, Pierre-Francois
中科院分区：
文献类型：
--
作者：
Marteau, Pierre-Francois
成功地将迭代时间弹性核平均（iTEKA）方法用于时间序列平均。在本文中，我们将其应用于GPS轨迹。关键的贡献是一个去噪过程，包括过采样方案，异常轨迹的检测和去除，核时间弹性平均方法，以及下采样作为后处理。在基准数据集上进行的实验表明，所提出的方法是有效的，并且优于基于中等或欧几里得平均方法的直接方法。
A method called iTEKA, which stands for iterative time elastic kernel averaging, was successfully used for averaging time series. In this paper, we adapt it to GPS trajectories. The key contribution is a denoising procedure that includes an over-sampling scheme, the detection and removal of outlier trajectories, a kernelized time elastic averaging method, and a down-sampling as post-processing. The experiment carried out on benchmark datasets showed that the proposed procedure is effective and outperforms straightforward methods based on medoid or Euclidean averaging approaches.