With the rise of end-to-end learning through deep learning, person detectors
and re-identification (ReID) models have recently become very strong.
Multi-camera multi-target (MCMT) tracking has not fully gone through this
transformation yet. We intend to take another step in this direction by
presenting a theoretically principled way of integrating ReID with tracking
formulated as an optimal Bayes filter. This conveniently side-steps the need
for data-association and opens up a direct path from full images to the core of
the tracker. While the results are still sub-par, we believe that this new,
tight integration opens many interesting research opportunities and leads the
way towards full end-to-end tracking from raw pixels.