EVENT DETECTION AND
RECOGNITION USING HMM WITH WHISTLE SOUNDS
In this paper, we propose a
new method to detect and recognize events robustly in a soccer game. Based on
the players density and speed, the events are detected and recognized using
Hidden Markov Model (HMM). However, it is difficult to detect "free
kick" and "throw in" because these events occur anytime and
anywhere. In a soccer game, some event occurs when the referee blows a whistle
or a ball is out of field. Therefore, we improve the detection accuracy of the
events such as "free kick" and "throw in" by using these
information when they occur. Also, event recognition is performed by an
integration method of the results obtained using two types of HMMs: one is for
players and the other is for a ball.
Published in:
Date of
Conference:
2-5 Dec. 2013
Page(s):
14 - 21
INSPEC Accession
Number:
14064357
Conference
Location :
Kyoto
Digital Object
Identifier :
Publisher:
IEEE
