Abstract
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.
Originalsprog | Engelsk |
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Tidsskrift | Sensors |
Vol/bind | 14 |
Udgave nummer | 8 |
Sider (fra-til) | 13679-13691 |
Antal sider | 13 |
ISSN | 1424-8220 |
DOI | |
Status | Udgivet - 29 jul. 2014 |