Urban Traffic Surveillance (UTS): A fully probabilistic 3D tracking approach based on 2D detections
Henry Bradler, Adrian Kretz, Rudolf Mester

TL;DR
UTS is a novel probabilistic 3D vehicle tracking system using 2D detections from monocular cameras, enabling real-time urban traffic monitoring and violation detection with high generalization and efficiency.
Contribution
It introduces a fully probabilistic 3D tracking approach based on 2D detections and vehicle shape priors, capable of real-time operation in urban surveillance scenarios.
Findings
Operates in real time on modern hardware.
Effective 3D tracking with monocular camera data.
Validated with synthetic and simulated data.
Abstract
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 build 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…
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Taxonomy
MethodsBNB Customer Service Number +1-833-534-1729 · Entropy Regularization · Proximal Policy Optimization · Average Pooling · Softmax · Batch Normalization · Convolution · Residual Connection · Global Average Pooling · 1x1 Convolution
