Intelligent ROI-Based Vehicle Counting Framework for Automated Traffic Monitoring
Accurate vehicle counting through video surveillance is crucial for efficient traffic management. However, achieving high counting accuracy while ensuring computational efficiency remains a challenge. To address this, we propose a fully automated, video-based vehicle counting framework designed to optimize both computational efficiency and counting accuracy. Our framework operates in two distinct phases: \textit{estimation} and \textit{prediction}. In the estimation phase, the optimal region of interest (ROI) is automatically determined using a novel combination of three models based on detection scores, tracking scores, and vehicle density. This adaptive approach ensures compatibility wi...
| Authors | Mohamed A. Abdelwahab, Zaynab Al-Ariny, Mahmoud Fakhry et al. |
|---|---|
| Primary category | cs.AI |
| Published | 14 April 2026 |
| Last updated at source | 14 April 2026 |
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