ACADSTAFF UGM
| Title | : | Vehicle Counting Framework for Intelligent Traffic Monitoring System |
| Author | : |
Vido Valianto (1) Wahyono, Ph.D. (2) |
| Date | : | 31 2019 |
| Keyword | : | Kalman Filter,vehicle counting,traffic monitoring,vehicle detection,CCTV Kalman Filter,vehicle counting,traffic monitoring,vehicle detection,CCTV |
| Abstract | : | Regulating the number of vehicles on the road is one of the solutions to the traffic problems. It is done by counting the number of vehicles passing the road. However, the lack of data and the manual observation to the closed-circuit television (CCTV) cameras make this solution becomes unreliable. Thus, in this paper, the system to automatically detect and count the number of vehicles is presented. The method based on a computer vision approach which utilized background modeling and Kalman filter. The method will be evaluated using real CCTV data which were obtained in Sukoharjo north of Gas Stations (POM) Bulakrejo at 05.00 am until 5.00 pm. The CCTV produces a bird-view angle video with a resolution of 1280 × 720. The experimental result shows that our method obtains only 20% of false positive and 10% of a false negative in counting the vehicle. |
| Group of Knowledge | : | |
| Level | : | Internasional |
| Status | : |
Published
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