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2004
Springer

Tracking the Evolution of a Tennis Match Using Hidden Markov Models

10 years 5 months ago
Tracking the Evolution of a Tennis Match Using Hidden Markov Models
The creation of a cognitive perception systems capable of inferring higher-level semantic information from low-level feature and event information for a given type of multimedia content is a problem that has attracted many researchers’ attention in recent years. In this work, we address the problem of automatic interpretation and evolution tracking of a tennis match using standard broadcast video sequences as input data. The use of a hierarchical structure consisting of Hidden Markov Models is proposed. This will take low-level events as its input, and will produce an output where the final state will indicate if the point is to be awarded to one player or another. Using hand-annotated data as input for the classifier described, we have witnessed 100% of the points correctly awarded to the players.
Ilias Kolonias, William J. Christmas, Josef Kittle
Added 02 Jul 2010
Updated 02 Jul 2010
Type Conference
Year 2004
Where SSPR
Authors Ilias Kolonias, William J. Christmas, Josef Kittler
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