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arXiv · 1609.01775

Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking

Ergys Ristani·Francesco Solera·Roger S. Zou·Rita Cucchiara·Carlo Tomasi
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Abstract

To help accelerate progress in multi-target, multi-camera tracking systems, we present (i) a new pair of precision-recall measures of performance that treats errors of all types uniformly and emphasizes correct identification over sources of error; (ii) the largest fully-annotated and calibrated data set to date with more than 2 million frames of 1080p, 60fps video taken by 8 cameras observing more than 2,700 identities over 85 minutes; and (iii) a reference software system as a comparison baseline. We show that (i) our measures properly account for bottom-line identity match performance in the multi-camera setting; (ii) our data set poses realistic challenges to current trackers; and (iii) the performance of our system is comparable to the state of the art.

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Ergys Ristani, Francesco Solera, Roger S. Zou, Rita Cucchiara, Carlo Tomasi. 2016-09-06. Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking. https://arxiv.org/abs/1609.01775

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