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A statistical-driven approach for automatic classification of events in AFL video highlights

Tjondronegoro, Dian, Chen, Yi-Ping Phoebe and Pham, Binh 2005, A statistical-driven approach for automatic classification of events in AFL video highlights, in Proceedings of the twenty eighth Australasian Computer Science Conference (ACSC 2005) Newcastle, Australia, January, 2005, Australian Computer Society, Sydney, N.S.W., pp. 209-218.

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Title A statistical-driven approach for automatic classification of events in AFL video highlights
Author(s) Tjondronegoro, Dian
Chen, Yi-Ping Phoebe
Pham, Binh
Conference name Australasian Computer Science Conference (28th : 2005 : Newcastle, N.S.W.)
Conference location Newcastle, Australia
Conference dates January 2005
Title of proceedings Proceedings of the twenty eighth Australasian Computer Science Conference (ACSC 2005) Newcastle, Australia, January, 2005
Editor(s) Estivill-Castro, Vladimir
Publication date 2005
Conference series Australasian Computer Science Conference
Start page 209
End page 218
Publisher Australian Computer Society
Place of publication Sydney, N.S.W.
Keyword(s) sports video summarisation
semantic analysis
self-consumable highlights
algorithms
AFL
Summary Due to the repetitive and lengthy nature, automatic content-based summarization is essential to extract a more compact and interesting representation of sport video. State-of-the art approaches have confirmed that high-level semantic in sport video can be detected based on the occurrences of specific audio and visual features (also known as cinematic). However, most of them still rely heavily on manual investigation to construct the algorithms for highlight detection. Thus, the primary aim of this paper is to demonstrate how the statistics of cinematic features within play-break sequences can be used to less-subjectively construct highlight classification rules. To verify the effectiveness of our algorithms, we will present some experimental results using six AFL (Australian Football League) matches from different broadcasters. At this stage, we have successfully classified each play-break sequence into: goal, behind, mark, tackle, and non-highlight. These events are chosen since they are commonly used for broadcasted AFL highlights. The proposed algorithms have also been tested successfully with soccer video.
ISBN 1920682201
9781920682200
Language eng
Field of Research 080199 Artificial Intelligence and Image Processing not elsewhere classified
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2005, Australian Computer Society
Persistent URL http://hdl.handle.net/10536/DRO/DU:30009699

Document type: Conference Paper
Collections: School of Information Technology
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