LMGP: Lifted Multicut Meets Geometry Projections for Multi-Camera Multi-Object Tracking. (arXiv:2111.11892v3 [cs.CV] UPDATED)

Multi-Camera Multi-Object Tracking is currently drawing attention in the
computer vision field due to its superior performance in real-world
applications such as video surveillance in crowded scenes or in wide spaces. In
this work, we propose a mathematically elegant multi-camera multiple object
tracking approach based on a spatial-temporal lifted multicut formulation. Our
model utilizes state-of-the-art tracklets produced by single-camera trackers as
proposals. As these tracklets may contain ID-Switch errors, we refine them
through a novel pre-clustering obtained from 3D geometry …

arxiv cv geometry tracking