论文标题
基于音频的车辆速度估计的数据集
A dataset for audio-video based vehicle speed estimation
论文作者
论文摘要
出于多种原因，公路车辆的准确速度估计很重要。一种是速度限制执法，这代表了减少交通事故和死亡的关键工具。与其他研究领域和域相比，用于车速估计的可用数据集数量仍然非常有限。我们提出了一个以已知速度通过相机通过相机的单车的跨道录像录音数据集，并通过车载巡航控制稳定。该数据集包含13辆汽车，在制造商，生产年度，发动机类型，电源和传输方面被选为尽可能多的多样化，总计$ 400 $注释的Andio-Video录音。该数据集已完全可用，并旨在作为公共基准，以促进音频视频估算的研究。除数据集外，我们还提出了一种交叉验证策略，可以在机器学习模型中用于车速估计。提出了两种数据集的训练验证拆分方法。
Accurate speed estimation of road vehicles is important for several reasons. One is speed limit enforcement, which represents a crucial tool in decreasing traffic accidents and fatalities. Compared with other research areas and domains, the number of available datasets for vehicle speed estimation is still very limited. We present a dataset of on-road audio-video recordings of single vehicles passing by a camera at known speeds, maintained stable by the on-board cruise control. The dataset contains thirteen vehicles, selected to be as diverse as possible in terms of manufacturer, production year, engine type, power and transmission, resulting in a total of $ 400 $ annotated audio-video recordings. The dataset is fully available and intended as a public benchmark to facilitate research in audio-video vehicle speed estimation. In addition to the dataset, we propose a cross-validation strategy which can be used in a machine learning model for vehicle speed estimation. Two approaches to training-validation split of the dataset are proposed.
