Performance measures and a data set for multi-target, multi-camera tracking

Published

Conference Paper

© Springer International Publishing Switzerland 2016. 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.

Full Text

Duke Authors

Cited Authors

  • Ristani, E; Solera, F; Zou, R; Cucchiara, R; Tomasi, C

Published Date

  • January 1, 2016

Published In

Volume / Issue

  • 9914 LNCS /

Start / End Page

  • 17 - 35

Electronic International Standard Serial Number (EISSN)

  • 1611-3349

International Standard Serial Number (ISSN)

  • 0302-9743

International Standard Book Number 13 (ISBN-13)

  • 9783319488806

Digital Object Identifier (DOI)

  • 10.1007/978-3-319-48881-3_2

Citation Source

  • Scopus