Urban Traffic Surveillance (UTS) is a surveillance system based on a monocular and calibrated video camera that detects vehicles in an urban traffic scenario with dense traffic on multiple lanes and vehicles performing sharp turning maneuvers. UTS then tracks the vehicles using a 3D bounding box representation and a physically reasonable 3D motion model relying on an Unscented Kalman filter based approach. Since UTS recovers positions, shape and motion information in a three-dimensional world coordinate system, it can be employed to recognize diverse traffic violations or to supply intelligent vehicles with valuable traffic information. We rely on YOLOv3 as a detector yielding 2D bounding boxes and class labels for each vehicle. A 2D detector renders our system much more independent to different camera perspectives as a variety of labeled training data is available. This allows for a good generalization while also being more hardware efficient. The task of 3D tracking based on 2D detections is supported by integrating class specific prior knowledge about the vehicle shape. We quantitatively evaluate UTS using self generated synthetic data and ground truth from the CARLA simulator, due to the non-existence of datasets with an urban vehicle surveillance setting and labeled 3D bounding boxes. Additionally, we give a qualitative impression of how UTS performs on real-world data. Our implementation is capable of operating in real time on a reasonably modern workstation. To the best of our knowledge, UTS is the only 3D vehicle tracking system in a surveillance scenario (static camera observing moving targets).
翻译:城市交通监视(UTS)是一个监测系统,其基础是单向和校准的摄像机,在城市交通情况中检测车辆,多行道和车辆的交通流量密集,并进行快速转弯操作。UTS随后使用3D捆绑盒代表器和一种基于不鼓励的Kalman过滤器的物理上合理的3D运动模型跟踪车辆。由于UTS在三维世界协调系统中恢复了位置、形状和运动信息,因此可以用来识别各种交通违规情况,或向智能车辆提供宝贵的交通信息。我们依靠YOLOv3作为检测器,产生2D捆绑箱和每部车辆的分类标签。2D探测器使我们的系统更加独立,以不同的摄像角度看待各种贴标签的培训数据。这样可以很好地进行概括,同时提高硬件效率。基于2D探测器的3D跟踪任务得到支持,只是将关于车辆形状的班级特定知识整合到现代车辆形状。我们用自制合成数据和CARD模拟器的地面观察仪生成的数据和地面真相进行定量评估。2D探测器使得我们的系统更加独立,因为我们的系统能够了解不同的摄像系统是如何在现实运行中进行。