Multi Person Tracking

Multi-person tracking (MPT) aims to automatically identify and track multiple individuals within a scene over time, a crucial task in various applications like surveillance, robotics, and sports analytics. Current research emphasizes robust tracking in challenging conditions (occlusions, similar appearances, diverse motions) using advanced techniques like transformer networks, reinforcement learning for efficient multi-camera systems, and hybrid approaches combining deep learning with classical methods for real-time performance. The development of large-scale, diverse datasets and improved evaluation metrics are driving progress, leading to more accurate and efficient MPT algorithms with significant implications for various fields.