Provident detection of other road users at night has the potential for increasing road safety. For this purpose, humans intuitively use visual cues, such as light cones and light reflections emitted by other road users to be able to react to oncoming traffic at an early stage. This behavior can be imitated by computer vision methods by predicting the appearance of vehicles based on emitted light reflections caused by the vehicle's headlights. Since current object detection algorithms are mainly based on detecting directly visible objects annotated via bounding boxes, the detection and annotation of light reflections without sharp boundaries is challenging. For this reason, the extensive open-source dataset PVDN (Provident Vehicle Detection at Night) was published, which includes traffic scenarios at night with light reflections annotated via keypoints. In this paper, we explore the potential of saliency-based approaches to create different object representations based on the visual saliency and sparse keypoint annotations of the PVDN dataset. For that, we extend the general idea of Boolean map saliency towards a context-aware approach by taking into consideration sparse keypoint annotations by humans. We show that this approach allows for an automated derivation of different object representations, such as binary maps or bounding boxes so that detection models can be trained on different annotation variants and the problem of providently detecting vehicles at night can be tackled from different perspectives. With that, we provide further powerful tools and methods to study the problem of detecting vehicles at night before they are actually visible.
翻译:夜间对其他道路使用者的节约储金探测具有提高道路安全的潜力。为此目的,人类直觉地使用视觉提示,例如其他道路使用者发射的灯锥和光反射器等视觉提示,以便能够在早期对交通的到来作出反应。这种行为可以通过计算机视觉方法模仿,预测车辆的出现,其依据是车头灯造成的射出的光反射。由于目前的物体探测算法主要基于直接可见的物体通过捆绑箱附加注释,因此光反射的探测和注释具有挑战性。因此,在夜视前公布广泛的开放源数据集PVDN(夜视车辆探测仪),其中包括夜间的光反射情景,通过关键点附加注释。在本文中,我们探索了根据PVDN数据集的视觉突出度和稀少关键点说明制作不同物体的突出方式。为此,我们把Boolean的地图突出度的一般概念推广到背景觉察目标上,在夜视前的视野下进行广泛的开放源数据集PVDN(夜间探测) (夜视器探测) (夜视探测) (夜视器探测) (夜视探测) (夜视探测) (夜视器探测) (夜视定位探测器探测) 之前的深度定位定位定位分析方法,我们可以通过对不同的飞行器进行不同的定位分析分析, 定位分析。