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2016 | OriginalPaper | Buchkapitel

Performance Measures and a Data Set for Multi-target, Multi-camera Tracking

verfasst von : Ergys Ristani, Francesco Solera, Roger Zou, Rita Cucchiara, Carlo Tomasi

Erschienen in: Computer Vision – ECCV 2016 Workshops

Verlag: Springer International Publishing

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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 1080 p, 60 fps video taken by 8 cameras observing more than 2,700 identities over 85 min; 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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Vorheriges Kapitel Real-Time Semantic Segmentation with Label Propagation

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Titel: Performance Measures and a Data Set for Multi-target, Multi-camera Tracking
verfasst von: Ergys Ristani
Francesco Solera
Roger Zou
Rita Cucchiara
Carlo Tomasi
Verlag: Springer International Publishing
Buch: Computer Vision – ECCV 2016 Workshops
Print ISBN: 978-3-319-48880-6

Electronic ISBN: 978-3-319-48881-3

Copyright-Jahr: 2016
DOI: https://doi.org/10.1007/978-3-319-48881-3_2

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