the 22 body joints of each person and fit a tight bounding box around them. Then, we enlarge the bounding box by 5% in each direction to capture the whole extent of a person (as the joints do not lie on the boundaries). This procedure is very similar to the one employed to generate bounding boxes for PoseTrack 2018 [@andriluka2018posetrack]. Finally, we disregard the bounding boxes that are too small ($<25 \times 50$ pixels), that are too far away from the camera ($>25$ meters) and that contain less than 50% of the body joints. As we downsample all the high-resolution 1080p videos to have a short side of $900$, these small and hard bounding boxes become almost untrackable.

Evaluation metric: TrackAP
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In sec. \[sec:mot\] we evaluated on the metrics defined by MOTChallenge. Among those that we reported, MOTA is considered the most important and is often the only metric highlighted. MOTA is indeed a good metric for tracking, but it over-emphasizes the accuracy of the detections of a track, rather than the temporal consistency of the track itself. For example, for MOTA, localizing all people correctly (fig. \[figure:mota\_ap\][b]{}) is more important (i.e., it yields better results) than assigning the 