Multi Camera Tracking

Multi-camera tracking (MCT) aims to identify and track objects across multiple, often overlapping, camera views, improving accuracy and robustness compared to single-camera systems. Current research emphasizes developing end-to-end trainable models, often leveraging transformer architectures or incorporating sophisticated data association techniques that fuse visual and motion information to handle occlusions and appearance changes. This field is crucial for applications like autonomous driving, video surveillance, and human-computer interaction, driving the need for larger, more realistic datasets and efficient algorithms suitable for real-time deployment.