@inproceedings{33f1f790ee3f439b80c96de4f7a89b05,
title = "Estimating the Number of Soccer Players using Simulation-based Occlusion Handling",
abstract = "Estimating the number of soccer players is crucial in- formation for occupancy analysis and other monitoring ac- tivities in sports analysis. It depends on player detection in the field that should be independent of the environment and light conditions. Thermal cameras are therefore a bet- ter option over normal RGB cameras. Detection of non- occluded players is doable but precise estimation of number of the players in groups is hard to achieve. Here we pro- pose a novel method for estimating number of the players in groups using computer graphics and virtual simulations. Occlusion conditions are first classified by using distinctive set of features trained by a bagged tree classifier. Estima- tion of the number of players is then performed by maximum likelihood of probability density based approach to further classify the occluded players. The results show that the im- plemented strategy is capable of providing precise results even during occlusion conditions.",
author = "Huda, {Noor Ul} and Jensen, {Kasper Halkj{\ae}r} and Rikke Gade and Moeslund, {Thomas B.}",
year = "2018",
doi = "10.1109/CVPRW.2018.00236",
language = "English",
isbn = "978-1-5386-6101-7",
series = "IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)",
publisher = "IEEE",
pages = "1937--1946",
booktitle = "2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)",
address = "United States",
note = "IEEE Conference on Computer Vision and Pattern Recognition, 2018, IEEE CVPR 2018 ; Conference date: 18-06-2018 Through 22-06-2018",
}