Automatic detection of ball and players in soccer games

Automatic analysis of ball and player position from a match video is an essential image and video processing topic. Moreover, it also plays a significant role in professional coaching and training of soccer nowadays. This project aims to study the success and failure of past researchers and develop...

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Main Author: Yu, Kangran.
Other Authors: Foo Say Wei
Format: Final Year Project
Language:English
Published: 2011
Subjects:
Online Access:http://hdl.handle.net/10356/46030
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-460302023-07-07T17:19:34Z Automatic detection of ball and players in soccer games Yu, Kangran. Foo Say Wei School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems Automatic analysis of ball and player position from a match video is an essential image and video processing topic. Moreover, it also plays a significant role in professional coaching and training of soccer nowadays. This project aims to study the success and failure of past researchers and develop new methodologies that perform ball and players’ positions detection from a video file. The detection is discussed under two occasions, when target is not overlapped by other objects and when occlusion takes place. Regarding these scenarios, two different Matlab based algorithms are established to accomplish detection/estimation of ball and players position. One of the methods is based on the intuitive image processing and a new roundness computation while the other algorithm executes candidate segments comparison by estimating covariance matrices and eigenvectors. The basic theory of multivariate distribution in statistics and probabilities is also implemented in the latter algorithm. After all, two algorithms are constructed into one function to perform active and reliable detection in both occlusion and non-overlapped cases. Additionally, this project only focuses on detection of objects on a 2-dimensional space, thus match videos of Barcelona F.C., Arsenal F.C., and Real Madrid are selected as samples thanks to their relatively fluid and ground based match flow. Bachelor of Engineering 2011-06-27T09:02:04Z 2011-06-27T09:02:04Z 2011 2011 Final Year Project (FYP) http://hdl.handle.net/10356/46030 en Nanyang Technological University 63 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Yu, Kangran.
Automatic detection of ball and players in soccer games
description Automatic analysis of ball and player position from a match video is an essential image and video processing topic. Moreover, it also plays a significant role in professional coaching and training of soccer nowadays. This project aims to study the success and failure of past researchers and develop new methodologies that perform ball and players’ positions detection from a video file. The detection is discussed under two occasions, when target is not overlapped by other objects and when occlusion takes place. Regarding these scenarios, two different Matlab based algorithms are established to accomplish detection/estimation of ball and players position. One of the methods is based on the intuitive image processing and a new roundness computation while the other algorithm executes candidate segments comparison by estimating covariance matrices and eigenvectors. The basic theory of multivariate distribution in statistics and probabilities is also implemented in the latter algorithm. After all, two algorithms are constructed into one function to perform active and reliable detection in both occlusion and non-overlapped cases. Additionally, this project only focuses on detection of objects on a 2-dimensional space, thus match videos of Barcelona F.C., Arsenal F.C., and Real Madrid are selected as samples thanks to their relatively fluid and ground based match flow.
author2 Foo Say Wei
author_facet Foo Say Wei
Yu, Kangran.
format Final Year Project
author Yu, Kangran.
author_sort Yu, Kangran.
title Automatic detection of ball and players in soccer games
title_short Automatic detection of ball and players in soccer games
title_full Automatic detection of ball and players in soccer games
title_fullStr Automatic detection of ball and players in soccer games
title_full_unstemmed Automatic detection of ball and players in soccer games
title_sort automatic detection of ball and players in soccer games
publishDate 2011
url http://hdl.handle.net/10356/46030
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