Vision based vehicle counting at crowded intersections
| dc.contributor.author | Benslimane, Echyma | |
| dc.contributor.author | Gherabi, Amira | |
| dc.contributor.author | Reporter: Ghemougui, Abdessettar | |
| dc.date.accessioned | 2022-07-13T10:44:51Z | |
| dc.date.available | 2022-07-13T10:44:51Z | |
| dc.date.issued | 2022-06-10 | |
| dc.description.abstract | Traffic congestion has a significant negative impact on the environment and on people, and one of the most important reasons is poor control of traffic signals. Vehicle counting in crowded intersections is a crucial element of any traffic optimization solution. In this work, we propose a computer vision based vehicle counting method. We adopts YOLO-v3 as vehicle de tector, we added a series of post-processing mechanisms to achieve robust vehicle counting. We created framework to asemi-utomatically generate a dedecated dataset for vehicle counting, this dataset can be later used as training data for new maching learning based solutions. | en_US |
| dc.identifier.uri | https://repository.univ-msila.dz/handle/123456789/30263 | |
| dc.language.iso | en | en_US |
| dc.publisher | UNIVERSITY of M'SILA | en_US |
| dc.subject | Computer vision; Intelligent traffic signal control system; Vehicle counting. | en_US |
| dc.title | Vision based vehicle counting at crowded intersections | en_US |
| dc.type | Thesis | en_US |