论文标题
从人行检测到人行横道估计：EM算法和对不同数据集的分析
From Pedestrian Detection to Crosswalk Estimation: An EM Algorithm and Analysis on Diverse Datasets
论文作者
论文摘要
在这项工作中，我们使用已加工后的LiDar Point云或相机图像的行人检测来估算标记和未标记的行人人行横道的角点和线性交叉段的EM算法。我们通过分析包含四个数据收集的三个现实世界数据集来证明算法性能，用于四角和两角，带有标记和未标记的人类人行横道。此外，我们还包括一个Python视频工具，以在我们的公共源代码中可视化交叉参数估计，行人轨迹和相位间隔。
In this work, we contribute an EM algorithm for estimation of corner points and linear crossing segments for both marked and unmarked pedestrian crosswalks using the detections of pedestrians from processed LiDAR point clouds or camera images. We demonstrate the algorithmic performance by analyzing three real-world datasets containing multiple periods of data collection for four-corner and two-corner intersections with marked and unmarked crosswalks. Additionally, we include a Python video tool to visualize the crossing parameter estimation, pedestrian trajectories, and phase intervals in our public source code.
