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from K strong clusters. The algorithm to detect the emotional scenes is shown in
Algorithm 3.
Algorithm 3. Emotional scene detection
Notations:
E i :The i -th emotional scene in which the facial expression c appears.
first ( E i )
: The frame number of the beginning frame in E i .
last ( E i )
: The frame number of the ending frame in E i .
E i )
: The length of E i . It is equivalent to last
E i )
E i )
length
(
(
first
(
1.
# int ( E i ) : The number of emotional scenes integrated into E i .
# nonemo
: The number of nonemotional frames in E i . Note that a nonemotional
frame means that the facial expression appears in that frame is different from c .
dist ( E i , E j ) : The distance between E i
E i )
(
and E j
( i < j ) . It is equivalent to first ( E j )
last ( E i ) 1.
Initialize: For each frame image classified into the facial expression c , initialize according
to Equation (5):
first ( E i )= last ( E i )= c i , # int ( E i )= 0 ,
# nonemo ( E i )= 0 ,
length ( E i )= 1 , ( 1 i M c )
(5)
where, c i is the frame number of the i -th emotional frame in the video. M c is the number
of emotional frames. An emotional frame is the frame classified into c . That is, each
emotional scene consists of a single emotional frame.
Procedure:
1: Find i in accordance with Equation (6):
i = argmin
i
dist ( E i , E i + 1 )
E i )
E i )
length
(
# nonemo
(
s . t . dist ( E i , E i + 1 )
# int ( E i )+ 1
length ( E i + 1 )
# nonemo ( E i + 1 )
# int ( E i + 1 )+ 1
dist ( E i , E i + 1 )
(6)
2: If there is no i that satisfies Equation (6), finish the procedure and output current emo-
tional scenes. Otherwise, proceed to step 3.
3: Integrate E i + 1
into E i
by updating E i
as follows:
last ( E i ) last ( E i + 1 ) , # int ( E i ) # int ( E i )+ 1 ,
# nonemo ( E i ) # nonemo ( E i )+ first ( E i + 1 ) last ( E i ) 1
Note that length ( E i ) is also updated due to the update of last ( E i ) .
4: Delete E i + 1
and renumber the subscripts of E i
so that the emotional scenes become
E i ,..., E c M c 1 .
5: M c M c 1 and return to step 1.
 
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