Global Data Association for Multi-Object Tracking Using Network flows


Abstract

We propose a network flow based optimization method for data association needed for multiple object tracking. The maximum-a-posteriori (MAP) data association problem is mapped into a cost-flow network with a non-overlap constraint on trajectories.


Maintained by Qian Yu