Multi Camera Vehicle Tracking

Multi-camera vehicle tracking aims to automatically identify and follow vehicles across multiple, often overlapping, camera views, enabling comprehensive traffic monitoring and analysis. Current research emphasizes efficient algorithms, such as graph-based methods and transformer networks, to address challenges like data association across cameras and handling occlusions, often incorporating self-supervised learning to reduce reliance on manual annotation. This technology is crucial for applications ranging from intelligent transportation systems and autonomous driving to urban planning and air quality monitoring, offering significant improvements in traffic management, safety, and environmental analysis.