of a newly localized person. In practice, the solver postpones this decision to after the new localized person has been tracked for a few frames. Then, it computes the average $\ell_2$ embedding distance between the 5 most similar bounding boxes from the new and old tracks. If this value is less than 0.5, the track gets reinstated. Otherwise, a new track is initiated. To enable this feature comparison, our solver maintains and updates a small buffer that caches the embeddings of the terminated and ongoing tracks. We set the size of this buffer to 30 seconds, which offers a good trade-off between low memory consumption and enough temporal information.

Results on MOTChallenge {#sec:mot}
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#### Dataset.

MOTChallenge [@milan2016mot16] is the most widely-adopted multi-person tracking benchmark. It consists of 7 training and 7 test videos that capture scenes from different camera angles. MOT is challenging, as it contains several occluded or truncated individuals and a large number of people to track. We experiment with two tracking benchmarks in the MOTChallenge: MOT16 and MOT17. The official tracking task consists of correctly linking (tracking) a set of provided per-frame person detections over the whole video. Both sets contain exactly the same videos, but 