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HOTA: A Higher Order Metric for Evaluating Multi-object Tracking
Multi-object tracking (MOT) has been notoriously difficult to evaluate. Previous metrics overemphasize the importance of either detection or association. To address this, we present a novel MOT evaluation metric, higher order tracking accuracy (HOTA), which explicitly balances the effect of performi...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7881978/ https://www.ncbi.nlm.nih.gov/pubmed/33642696 http://dx.doi.org/10.1007/s11263-020-01375-2 |
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author | Luiten, Jonathon Os̆ep, Aljos̆a Dendorfer, Patrick Torr, Philip Geiger, Andreas Leal-Taixé, Laura Leibe, Bastian |
author_facet | Luiten, Jonathon Os̆ep, Aljos̆a Dendorfer, Patrick Torr, Philip Geiger, Andreas Leal-Taixé, Laura Leibe, Bastian |
author_sort | Luiten, Jonathon |
collection | PubMed |
description | Multi-object tracking (MOT) has been notoriously difficult to evaluate. Previous metrics overemphasize the importance of either detection or association. To address this, we present a novel MOT evaluation metric, higher order tracking accuracy (HOTA), which explicitly balances the effect of performing accurate detection, association and localization into a single unified metric for comparing trackers. HOTA decomposes into a family of sub-metrics which are able to evaluate each of five basic error types separately, which enables clear analysis of tracking performance. We evaluate the effectiveness of HOTA on the MOTChallenge benchmark, and show that it is able to capture important aspects of MOT performance not previously taken into account by established metrics. Furthermore, we show HOTA scores better align with human visual evaluation of tracking performance. |
format | Online Article Text |
id | pubmed-7881978 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-78819782021-02-25 HOTA: A Higher Order Metric for Evaluating Multi-object Tracking Luiten, Jonathon Os̆ep, Aljos̆a Dendorfer, Patrick Torr, Philip Geiger, Andreas Leal-Taixé, Laura Leibe, Bastian Int J Comput Vis Article Multi-object tracking (MOT) has been notoriously difficult to evaluate. Previous metrics overemphasize the importance of either detection or association. To address this, we present a novel MOT evaluation metric, higher order tracking accuracy (HOTA), which explicitly balances the effect of performing accurate detection, association and localization into a single unified metric for comparing trackers. HOTA decomposes into a family of sub-metrics which are able to evaluate each of five basic error types separately, which enables clear analysis of tracking performance. We evaluate the effectiveness of HOTA on the MOTChallenge benchmark, and show that it is able to capture important aspects of MOT performance not previously taken into account by established metrics. Furthermore, we show HOTA scores better align with human visual evaluation of tracking performance. Springer US 2020-10-08 2021 /pmc/articles/PMC7881978/ /pubmed/33642696 http://dx.doi.org/10.1007/s11263-020-01375-2 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Luiten, Jonathon Os̆ep, Aljos̆a Dendorfer, Patrick Torr, Philip Geiger, Andreas Leal-Taixé, Laura Leibe, Bastian HOTA: A Higher Order Metric for Evaluating Multi-object Tracking |
title | HOTA: A Higher Order Metric for Evaluating Multi-object Tracking |
title_full | HOTA: A Higher Order Metric for Evaluating Multi-object Tracking |
title_fullStr | HOTA: A Higher Order Metric for Evaluating Multi-object Tracking |
title_full_unstemmed | HOTA: A Higher Order Metric for Evaluating Multi-object Tracking |
title_short | HOTA: A Higher Order Metric for Evaluating Multi-object Tracking |
title_sort | hota: a higher order metric for evaluating multi-object tracking |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7881978/ https://www.ncbi.nlm.nih.gov/pubmed/33642696 http://dx.doi.org/10.1007/s11263-020-01375-2 |
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