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Na educação, poucos trabalhos abordando reconhecimento de expressões faciais
foram encontrados. Um dos trabalhos relacionados foi proposto por Changjun et al
(2011). Eles fizeram um sistema de reconhecimento de expressões faciais em tempo real
utilizando um classificador de máquina de vetores de suporte (Support Vector Machines
- SVM), com o objetivo de estimar o estado afetivo dos alunos que utilizam um sistema
de Ensino a Distância (EaD) baseado em computação afetiva. Um rastreador de faces
reúne um conjunto de características de deslocamentos de movimento da face no
sistema de EaD. Estas características são posteriormente utilizadas para treinar um
classificador SVM para aprender a reconhecer expressões emocionais. Em seguida, o
estado emocional é avaliado e compreendido.
Changjun et al (2011) fizeram treinamentos do algoritmo SVM com 100
imagens faciais de 15 alunos. Estas foram selecionadas aleatoriamente a partir do banco
de dados, incluindo seis emoções básicas e neutras como um conjunto de treinamento.
Depois utilizou 265 imagens faciais de 42 pessoas, como conjunto de teste. O modelo
de sistema de EaD, proposto por Changjun et al (2011), com base em computação
afetiva atingiu uma taxa de reconhecimento total de 84,55%.
No trabalho proposto, apresenta-se um sistema de reconhecimento de expressões
faciais que inferi as emoções alegria, tristeza, raiva, e desgosto. Para isso, utilizou o
sistema psicológico de codificação facial FACS, o qual rastreia todos os movimentos
musculares faciais nas suas respectivas Unidades de Ações (UAs) [Ekman et al., 2002].
Foram aplicadas regras que verificam a deformação geométrica da boca, olhos e
sobrancelhas para reconhecer as UAs presentes nas expressões faciais das emoções
inferidas. Para a detecção da face e rastreamentos dos pontos característicos da face
foram utilizados a técnica Viola-Jones [Viola; Jones, 2004] e o modelo CANDIDE-3
[Ahlberg, 2001].!
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Figura 3. Execução do rastreamento das características faciais.
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Figura 4. FCPs utilizados para o mapeamento das UAs.
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Tabela 1. Deslocamentos das deformações geométricas nas expressões faciais.
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Tabela 2. Critério de Reconhecimento dos UAs@!
469
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Tabela 3. Associação das seis expressões faciais com seus UAs e combinações.
Adaptado de Yongmian e Qiang (2005).
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471
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!
Tabela 4. Resultado da precisão das emoções!
!
!
R%-%! :%,"! )"'! %7)"'.(,(! #(! 6(7"2(! F;! (! "C:'"))I%! -(/)! (-7>3=(! <($/(2! <%/!
,")3%)&%;! (:'")"#&(#,%! (! -"#%'! &(C(! ,"! ($"'&%;! =-(! ."X! B="! <%/! $2())/</$(,(!
/#$%''"&(-"#&"! #(! -(/%'/(! ,()! ."X")! $%-! (! "C:'"))I%! '(/.(! ";! "-! )"3=/,(;! #"=&'%@! +)!
"C:'"))1")! <($/(/)! B="! )"! )"3="-;! )I%! (! '(/.(! "! (2"3'/(;! $%-! =-(! &(C(! ,"! ($"'&%! ,"!
$2())/</$(0I%! )/-/2('! 5QLG9@! H)! '")=2&(,%)! ,()! "-%01");! #%! 3"'(2;! (:'")"#&(-V)"!
)(&/)<(&Z'/%!:('(!)=(!(:2/$(7/2/,(,"!(%!+[+!7()"(,%!"-!(3"#&");!:%/)!&%,()!()!"-%01")!
:%))=>'(-! &(C(! ,"! ($"'&%! ($/-(! ,"! ELG@! *-! .(2%'! $%-:('J."2! (! .J'/%)! )/)&"-()! ,"!
'"$%#D"$/-"#&%!,"!"-%01")!"C/)&"#&")!\O"7"!!"#$%&;!8LLA]@!!+24-!,/))%;!)"3=#,%!O"7"!!"#
$%! 58LLA9;! (! -4,/(! ,%! '"$%#D"$/-"#&%! ,"! "-%01")! <($/(/)! <"/&%)! :%'! D=-(#%)! 4! ,"!
(:'%C/-(,(-"#&"! EFG! ,"! :'"$/)I%;! "! B="! (23=#)! (23%'/&-%)! $%-:=&($/%#(/)! %7&4-!
)=$"))%! "#&'"! ^AG! "! QEG@! S%! "#&(#&%;! #%! $()%! ,"! %! )/)&"-(! '"$%#D"$"'! ()! "-%01")!
"''%#"(-"#&";!%!+[+!'"$"7"'J!(!"-%0I%!<(2)(!"!)"!'"):%#)(7/2/X('J!)"!&'(&(!,(!-")-(!
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!
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:%'!RD(#3K=#!!"#$%!58LMM9;!B="!:'%:=)"'(-!=-!)/)&"-(!,"!'"$%#D"$/-"#&%!,"!"-%01")!
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472
!
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646#3!;!,'!<=522>[email protected]#.64!4!&%&6'(#!B94B4&645!C#&'#,4!'(!9'79#&5!"4%!6'&6#,4!'(!)DD!
%(#7'.&!"#$%#%&!'(!E*!+69F&!,%('.&/'&0!,'!1D!%.,%GH,-4&5!#6%.7%.,4!-(!9'$4.:'$%('.64!
646#3!,'!<252>?!
Tabela 5. Matriz de confusão resultante dos testes do Sistema proposto.
!
!
I49!"%(5!'&6J!&'.,4!9'#3%K#,4!-(!'&6-,4!,'!$#&4!,4!&%&6'(#!,'!9'$4.:'$%('.64!
,'!'8B9'&&/'&!"#$%#%&!%.6'79#,4!#4!LML!$4(4!"49(#!,'!G#3%,#9!#!'"%$J$%#!,4&!9'&-36#,4&!
#B9'&'.6#,4&! .'&6'! 69#C#3:4?! @&&'! '&6-,4! ,'! $#&4! '&6J! %.6'79#,4! #4! B94N'64! %.6%6-3#,4!
³8P $JHQWH 3HGDJyJLFR ' GH $SRLR D (VWXGDQWHV GH 0HGLFLQD QD 5HVROXomR GH
3UREOHPDV QD ÈUHD GD 2QFRORJLD 8WLOL]DQGR D $SUHQGL]DJHP %DVHDGD HP 3UREOHPD´
#B94G#,4! B'34! OPQR! +O'.694! ,'! P.$4347%#! '! Q'(#64347%#0?! P! '&6-,4! ,'! $#&4! '&6J!
&'.,4! 9'#3%K#,4! $4(! '&6-,#.6'&! ,4! $-9&4! ,'! (',%$%.#5! &'.,4! '&&#! G#3%,#ST4! #B4%#,#!
B'34! OPQR?! U'&&#! 4$#&%T45! 4&! '&6-,#.6'&! '&6T4! -6%3%K#.,4! '&&'! &%&6'(#! ,'!
9'$4.:'$%('.64!,'!'(4S/'&!%.6'79#,4!$4(!4!LML!C#&'#,4!'(!#7'.6'&!,'!#B4%4!#!IVW5!
#! "%(! ,'! 9'&43G'9'(! B94C3'(#&! 9'3#$%4.#,4&! X! J9'#! ,'! P.$4347%#?! *'! #$49,4! $4(! 4&!
9'&-36#,4&! B9'3%(%.#9'&5! 4C6%,4&! ,'! &%(-3#S/'&! $4(! 1D! #3-.4&! ,'! (',%$%.#5! 4! &%&6'(#!
9'$4.:'$%('.64! ,'!'(4S/'&!#6%.7%-!-(#!6#8#!,'!9'$4.:'$%('.64!,'!#B948%(#,#('.6'!
<2>!'!-(!6'(B4!,'!9'&B4&6#!"%$#.,4!'(!(;,%#!,'!E!#!2!&'7-.,4&5!-6%3%K#.,4!#!Y.6'9.'6!
$4(! G'34$%,#,'!G#9%#.,4!,'!)!RCB&!+!"#$%&'(! B49!&'7-.,40!#!21)!ZCB&!+)&*+%&'(!B49!
&'7-.,40?! @&6'&! 9'&-36#,4&! &T4! $4.&%,'9#,4&! 'A-%G#3'.6'&! #4&! 6'&6'&! ,'&$9%64&! .'&6'!
69#C#3:4?! L3;(! ,%&&45! "4%! 4! 6'(B4! ,'! 9'&B4&6#&! "4%! $4.&%,'9#,4! '"%$#K5! B4%&! "4%!
$3#&&%"%$#,4!$4(4!C#%84!'!#$'%6JG'3!B'34&!'&6-,#.6'&!,4!$-9&4!,'!(',%$%.#!.#!9'&43-ST4!
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U'&6'! 69#C#3:45! &T4! 69#6#,4&! B94C3'(#&! ,'! %."'9F.$%#! ,'! '(4S/'&! ,'! %.,%GH,-4&! A-'!
%.6'9#7'(! '(! -(! LML5! -6%3%K#.,4! 4! 9'$4.:'$%('.64! ,'! '8B9'&&/'&! "#$%#%&?! L!
#C49,#7'(5! -6%3%K#.,4! 4! 9#&69'#('.64! ,'! $#9#$6'9H&6%$#&! "#$%#%&! B49! ('%4&! ,#&! 6;$.%$#&!
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6#%&!$4(4b!9'$-9&4&!,'!J-,%4!'!7'&64&?!!
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473
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