Intelligent transportation systems (ITS) have attracted considerable research attention in areas such as vehicle detection, recognition, and counting, and traffic parameter estimation. In light of the anticipated availability of low-cost hardware, as well as continuing progress in algorithmic research, computer vision has become a promising base technology for traffic sensing systems. Since vision sensors provide more information than the conventional sensors widely used in ITS, attention is now being focused on vision-based traffic surveillance systems.
This project aims to develop real-time traffic surveillance system for the detection, recognition, and tracking of multiple vehicles in the traffic videos. Following features can also be made s the part of this framework; Traffic Signal Light optimization using vehicle flow statistics, Identification of Speed Violation, Vehicle density estimation, Occlusive Vehicle Detection/recognition, Incident detection.
- Large-scale automated proactive road safety analysis using video data (link)
- Multiple Sensor Fusion and Classification for Moving Object Detection and Tracking (link)
- Looking at Vehicles on the Road: A Survey of Vision-Based Vehicle Detection, Tracking, and Behavior Analysis (link)
- A Review of Computer Vision Techniques for the Analysis of Urban Traffic (link)