menu ☰
menu ˟

A framework for event detection in field-sports video broadcasts based on SVM generated audio-visual feature model. Case-study: soccer video

Creator:

Sadlier, David A.; O'Connor, Noel E.; Murphy, Noel; Marlow, Seán;

Subject Keywords: Signal processing; Digital video; Event Detection; Field sports video; MPEG; Signal Processing; Support vector machine;
Region:
Description:

In this paper we propose a novel audio-visual feature-based framework, for event detection in field sports broadcast video. The system is evaluated via a case-study involving MPEG encoded soccer video. Specifically, the evidence gathered by various feature detectors is combined by means of a learning algorithm (a support vector machine), which infers the occurrence of an event, based on a model generated during a training phase, utilizing a corpus of 25 hours of content. The system is evaluated using 25 hours of separate test content. Following an evaluation of results obtained, it is shown for this case, that both high precision and recall statistics are achievable.

Format:

application/pdf

Related: http://doras.dcu.ie/399/1/iwssip_2004_2.pdf
Suggested citation:

Sadlier, David A.; O'Connor, Noel E.; Murphy, Noel; Marlow, Seán; . () A framework for event detection in field-sports video broadcasts based on SVM generated audio-visual feature model. Case-study: soccer video [Online]. Available from: http://publichealthwell.ie/node/617551 [Accessed: 26th June 2019].

  

View your saved citations and reading lists

Contributor:


 
Click here to view all the resources gathered from this organisation's website.