Automated Traffic Surveillance from an Aerial Camera Array
| 项目名称： | Automated Traffic Surveillance from an Aerial Camera Array |
| 摘要： | The overall goal of this O&E Grant is to design and develop an automated aerial network monitoring system concept that can identify and track individual vehicles through a network of 16 square miles in near real-time. The research includes the development of algorithms to map the locations of the vehicles and to extract traffic parameters for data mining purposes. Three (3) experimental vehicle tracking systems have been conceptualized and are being evaluated. They are: (1) Vehicle Tracking using a raw pixel appearance model/OpenStreetMap; (2) Surf feature tracking; and (3) Deep learning using the Caffe library (UC Berkeley). Based on results to date, the research team has selected a machine learning approach to detect and track vehicles in an aerial camera array video. The third system identified above, deep learning, appears more promising than other approaches--especially with challenging video sequences with seams and variation in luminance. |
| 状态： | Active |
| 资金： | 50000.00 |
| 资助组织： | Office of the Assistant Secretary for Research and Technology |
| 执行机构： | Clemson University |
| 开始时间： | 20140601 |
| 实际结束时间： | 20150831 |
| 主题领域： | Data and Information Technology；Highways；Operations and Traffic Management |
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