Paper Info
Title
Event detection based on generic characteristics of field-sports
Abstract
In this paper, we propose a generic framework for event detection in broadcast video of multiple different field-sports. Features indicating significant events are selected, and robust detectors built. These features are rooted in generic characteristics common to all genres of field-sports. The evidence gathered by the feature detectors is combined by means of a support vector machine, which infers the occurrence of an event based on a model generated during a training phase. The system is tested across multiple genres of field-sports including soccer, rugby, hockey and Gaelic football and the results suggest that high event retrieval and content rejection statistics are achievable.
Year
DOI
Venue
2005
10.1109/ICME.2005.1521534
ICME
Keywords
Field
DocType
content-based retrieval,digital video broadcasting,statistical analysis,support vector machines,video retrieval,video signal processing,content rejection statistics,event detection,event retrieval,field-sports,generic characteristics,support vector machine,training phase,video broadcasting
Broadcasting,Football,Computer vision,Signal processing,System testing,Computer science,Support vector machine,Event retrieval,Robustness (computer science),Artificial intelligence,Digital Video Broadcasting
Conference
ISBN
Citations 
PageRank 
0-7803-9331-7
2
0.37
References 
Authors
12
2
Name
Order
Citations
PageRank
David A. Sadlier1486.68
Noel E. O'Connor22137223.20