This page provides a set of measures proposed in [1] for the performance evaluation of multi-target video tracking algorithms.
Please send your feedback and comments to pft@spevi.org.
To evaluate multi-target video tracking results, one needs to quantify the accuracy of the estimated target-size and the cardinality error as well as measure the frequency of occurrence of ID changes. In this paper we survey existing multi-target tracking performance scores and, after discussing their limitations, we propose three parameter-independent measures for evaluating multi-target video tracking. The measures take into account target-size variations, combine accuracy and cardinality errors, quantify long-term tracking accuracy at different accuracy levels, and evaluate ID changes relative to the duration of the track in which they occur. We conduct an extensive experimental validation of the proposed measures by comparing them with existing ones and by evaluating four state-of-the-art trackers on challenging real-world publicly-available datasets. The software implementing the proposed measures is made available online to facilitate their use by the research community.
The code for the proposed measures can be downloaded from here (.zip, Matlab). The use of the software is free for research and educational purposes only at the condition of respecting the requested citation acknowledgment [1].
[1] T. Nawaz, F. Poiesi, A. Cavallaro, Measures of effective video tracking, IEEE Transactions on Image Processing, Vol. 23, Issue 1, pp. 376-388, January 2014 pdf