title: Thermal tracking of sports players.
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.
authors: Visual Analysis of People Lab, Aalborg University, Rendsburggade 14, 9000 Aalborg, Denmark. rg@create.aau.dk.
authors: Rikke
authors: R
authors: Gade
authors: Visual Analysis of People Lab, Aalborg University, Rendsburggade 14, 9000 Aalborg, Denmark. tbm@create.aau.dk.
authors: Thomas B
authors: TB
authors: Moeslund
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D010363:Pattern Recognition, Automated / Q000379:methods*; D013177:Sports; D014741:Video Recording / Q000379:methods*