<p>I know this is old but I see nobody mentioning HOTA (<a href="https://arxiv.org/pdf/2009.07736.pdf" rel="nofollow noreferrer">https://arxiv.org/pdf/2009.07736.pdf</a>). This has become the new standard for multi-object tracking as can be seen here: <a href="https://arxiv.org/abs/2202.13514" rel="nofollow noreferrer">https://arxiv.org/abs/2202.13514</a> and <a href="https://arxiv.org/pdf/2110.06864.pdf" rel="nofollow noreferrer">https://arxiv.org/pdf/2110.06864.pdf</a></p>
<p>MOTA and IDF1 overemphasize detection and association respectively. HOTA explicitly measures both types of errors and combines these in a balanced way. HOTA also incorporates measuring the localization accuracy of tracking results which isn’t present in either MOTA or IDF1.</p>
What are the best metrics for Multi-Object Tracking (MOT) evaluation and why?
<p>I want to compare multiple computer vision <strong>Multi-Object Tracking (MOT)</strong> methods on my own dataset, so first I want to choose the best metrics for this task. I have carried out some research in scientific literature and I come to the conclusion that there are three main metrics sets:</p>
<ol>
<li>Metrics from <a href="https://www.researchgate.net/publication/4246190_Tracking_of_Multiple_Partially_Occluded_Humans_based_on_Static_Body_Part_Detection" rel="nofollow noreferrer">&quot;Tracking of Multiple, Partially Occluded Humans based on Static Body Part
Detection&quot;</a></li>
<li><a href="https://www.researchgate.net/publication/26523191_Evaluating_multiple_object_tracking_performance_The_CLEAR_MOT_metrics" rel="nofollow noreferrer">CLEAR MOT metrics</a></li>
<li><a href="https://arxiv.org/abs/1609.01775" rel="nofollow noreferrer">ID scores</a></li>
</ol>
<p>Therefore, I wonder to which of the above metrics should I attach the greatest importance?</p>
<p>And I would like to ask if anyone has encountered a similar issue and has any thoughts on this topic that could justify and help me to choose the best metrics for the above task.</p>