You are here

Real-time event classification in field sport videos

Authors: 

Rafal Kapela, Aleksandra Świetlicka, Andrzej Rybarczyk, Krzysztof Kolanowski, Noel O'Connor

Publication Type: 
Refereed Original Article
Abstract: 
The paper presents a novel approach to real-time event detection in sports broadcasts. We present how the same underlying audio–visual feature extraction algorithm based on new global image descriptors is robust across a range of different sports alleviating the need to tailor it to a particular sport. In addition, we propose and evaluate three different classifiers in order to detect events using these features: a feed-forward neural network, an Elman neural network and a decision tree. Each is investigated and evaluated in terms of their usefulness for real-time event classification. We also propose a ground truth dataset together with an annotation technique for performance evaluation of each classifier useful to others interested in this problem.
Digital Object Identifer (DOI): 
10.1016/j.image.2015.04.005
Publication Status: 
Published
Date Accepted for Publication: 
Tuesday, 14 April, 2015
Publication Date: 
23/04/2015
Journal: 
Signal Processing: Image Communication
Volume: 
35
Pages: 
35–45
Research Group: 
Institution: 
Dublin City University (DCU)
Open access repository: 
Yes