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Thermal Tracking of Sports Players
We present here a real-time tracking algorithm for thermal video from a sports game. Robust detection of people includes routines for handling occlusions and noise before tracking each detected person with a Kalman filter. This online tracking algorithm is compared with a state-of-the-art offline mu...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4179012/ https://www.ncbi.nlm.nih.gov/pubmed/25076219 http://dx.doi.org/10.3390/s140813679 |
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author | Gade, Rikke Moeslund, Thomas B. |
author_facet | Gade, Rikke Moeslund, Thomas B. |
author_sort | Gade, Rikke |
collection | PubMed |
description | We present here a real-time tracking algorithm for thermal video from a sports game. Robust detection of people includes routines for handling occlusions and noise before tracking each detected person with a Kalman filter. This online tracking algorithm is compared with a state-of-the-art offline multi-target tracking algorithm. Experiments are performed on a manually annotated 2-minutes video sequence of a real soccer game. The Kalman filter shows a very promising result on this rather challenging sequence with a tracking accuracy above 70% and is superior compared with the offline tracking approach. Furthermore, the combined detection and tracking algorithm runs in real time at 33 fps, even with large image sizes of 1920 × 480 pixels. |
format | Online Article Text |
id | pubmed-4179012 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-41790122014-10-02 Thermal Tracking of Sports Players Gade, Rikke Moeslund, Thomas B. Sensors (Basel) Article We present here a real-time tracking algorithm for thermal video from a sports game. Robust detection of people includes routines for handling occlusions and noise before tracking each detected person with a Kalman filter. This online tracking algorithm is compared with a state-of-the-art offline multi-target tracking algorithm. Experiments are performed on a manually annotated 2-minutes video sequence of a real soccer game. The Kalman filter shows a very promising result on this rather challenging sequence with a tracking accuracy above 70% and is superior compared with the offline tracking approach. Furthermore, the combined detection and tracking algorithm runs in real time at 33 fps, even with large image sizes of 1920 × 480 pixels. MDPI 2014-07-29 /pmc/articles/PMC4179012/ /pubmed/25076219 http://dx.doi.org/10.3390/s140813679 Text en © 2014 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Article Gade, Rikke Moeslund, Thomas B. Thermal Tracking of Sports Players |
title | Thermal Tracking of Sports Players |
title_full | Thermal Tracking of Sports Players |
title_fullStr | Thermal Tracking of Sports Players |
title_full_unstemmed | Thermal Tracking of Sports Players |
title_short | Thermal Tracking of Sports Players |
title_sort | thermal tracking of sports players |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4179012/ https://www.ncbi.nlm.nih.gov/pubmed/25076219 http://dx.doi.org/10.3390/s140813679 |
work_keys_str_mv | AT gaderikke thermaltrackingofsportsplayers AT moeslundthomasb thermaltrackingofsportsplayers |