  Multi-Object Tracking (MOT) is most often approached in the
tracking-by-detection paradigm, where object detections are associated through
time. The association step naturally leads to discrete optimization problems.
As these optimization problems are often NP-hard, they can only be solved
exactly for small instances on current hardware. Adiabatic quantum computing
(AQC) offers a solution for this, as it has the potential to provide a
considerable speedup on a range of NP-hard optimization problems in the near
future. However, current MOT formulations are unsuitable for quantum computing
due to their scaling properties. In this work, we therefore propose the first
MOT formulation designed to be solved with AQC. We employ an Ising model that
represents the quantum mechanical system implemented on the AQC. We show that
our approach is competitive compared with state-of-the-art optimization-based
approaches, even when using of-the-shelf integer programming solvers. Finally,
we demonstrate that our MOT problem is already solvable on the current
generation of real quantum computers for small examples, and analyze the
properties of the measured solutions.
