Huang Xiaohui, He Pan, Rangarajan Anand, Ranka Sanjay
Department of Computer and Information Science and Engineering, University of Florida, 432 Newell Drive, CSE Building, Gainesville, FL 32611, USA.
J Imaging. 2022 Apr 6;8(4):101. doi: 10.3390/jimaging8040101.
Travel-time estimation of traffic flow is an important problem with critical implications for traffic congestion analysis. We developed techniques for using intersection videos to identify vehicle trajectories across multiple cameras and analyze corridor travel time. Our approach consists of (1) multi-object single-camera tracking, (2) vehicle re-identification among different cameras, (3) multi-object multi-camera tracking, and (4) travel-time estimation. We evaluated the proposed framework on real intersections in Florida with pan and fisheye cameras. The experimental results demonstrate the viability and effectiveness of our method.
交通流的行程时间估计是一个重要问题，对交通拥堵分析具有关键意义。我们开发了利用路口视频来识别跨多个摄像头的车辆轨迹并分析走廊行程时间的技术。我们的方法包括：（1）多目标单摄像头跟踪；（2）不同摄像头间的车辆重新识别；（3）多目标多摄像头跟踪；以及（4）行程时间估计。我们使用全景和鱼眼摄像头在佛罗里达州的实际路口对所提出的框架进行了评估。实验结果证明了我们方法的可行性和有效性。
