What Is Stopped Vehicle Detection?
Computer vision algorithms are widely used in traffic monitoring systems to automatically gain information on traffic scenes and trigger alarms on significant events and anomalies.
Real-time image processing of video feeds from surveillance cameras is used to detect road safety problems. AI models can detect stopped vehicles during traffic surveillance.
Features of Vehicle Detection with Deep Learning
Different vehicle types can be automatically detected and localized in video frames from surveillance cameras.
- Detection and classification of different vehicle types.
- Indication of specific areas to determine dangerous areas, for example, at an exit from a freeway or sidewalks.
- Automatically detect vehicle stops on the road (anomaly) within the specified areas.
Value of Real-time Anomaly Detection in Traffic Videos
Automated traffic control and analysis is an essential task for intelligent transportation systems. Anomaly detection in real-time videos is challenging due to the sparse occurrence of such events.
- Automated and scalable detection of safety problems without requiring personnel to monitor video streams constantly.
- Real-time performance and instant detection of anomalies and dangerous situations.
- Detection of traffic rule violations and accidents.
