RT Multi-Camera MoT System

Real-time Multi-Camera Multiple Object Tracking System


Tracking a crowd in 3D using multiple RGB cameras is a challenging task. Most previous multi-camera tracking algorithms are designed for offline setting and have high computational complexity. Robust real-time multi-camera 3D tracking is still an unsolved problem. In this work, we propose a novel end-to-end tracking pipeline, Deep Multi-Camera Tracking (DMCT), which achieves reliable real-time multi-camera people tracking. Our DMCT consists of 1) a fast and novel perspective-aware Deep GroudPoint Network, 2) a fusion procedure for groundplane occupancy heatmap estimation, 3) a novel Deep Glimpse Network for person detection and 4) a fast and accurate online tracker.


  • Demo video of our sytem on our dataset.
  • Demo video of our sytem on WILDTRACK.
  • Projection of human circle on each camera view
  • Examples

    Example images from a new environment with three network cameras (best viewed in color).


    Quanzeng You and Hao Jiang. Real-time 3D Deep Multi-Camera Tracking, arXiv preprint arXiv:2003.11753 (2020).