Scholars@Duke publication: Performance measures and a data set for multi-target, multi-camera tracking

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

Publication , Conference

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

Published in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

January 1, 2016

Published version (DOI)

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.

Duke Scholars

Author Carlo Tomasi Computer Science

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

10.1007/978-3-319-48881-3_2

EISSN

1611-3349

ISSN

0302-9743

Publication Date

January 1, 2016

Volume

9914 LNCS

Start / End Page

17 / 35

Related Subject Headings

Artificial Intelligence & Image Processing
46 Information and computing sciences

Citation

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Ristani, E., Solera, F., Zou, R., Cucchiara, R., & Tomasi, C. (2016). Performance measures and a data set for multi-target, multi-camera tracking. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9914 LNCS, pp. 17–35). https://doi.org/10.1007/978-3-319-48881-3_2

Ristani, E., F. Solera, R. Zou, R. Cucchiara, and C. Tomasi. “Performance measures and a data set for multi-target, multi-camera tracking.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9914 LNCS:17–35, 2016. https://doi.org/10.1007/978-3-319-48881-3_2.

Ristani E, Solera F, Zou R, Cucchiara R, Tomasi C. Performance measures and a data set for multi-target, multi-camera tracking. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2016. p. 17–35.

Ristani, E., et al. “Performance measures and a data set for multi-target, multi-camera tracking.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9914 LNCS, 2016, pp. 17–35. Scopus, doi:10.1007/978-3-319-48881-3_2.

Ristani E, Solera F, Zou R, Cucchiara R, Tomasi C. Performance measures and a data set for multi-target, multi-camera tracking. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2016. p. 17–35.

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

10.1007/978-3-319-48881-3_2

EISSN

1611-3349

ISSN

0302-9743

Publication Date

January 1, 2016

Volume

9914 LNCS

Start / End Page

17 / 35

Related Subject Headings

Artificial Intelligence & Image Processing
46 Information and computing sciences