Pengenalan ekspresi wajah menggunakan metode fisherface dengan pendekatan jaringan syaraf tiruan backpropagation
In daily lives, especially in interpersonal communication, face often used for expression. Facial expressions give information about the emotional state of the person. A facial expression is one of the behavioral characteristics. The components of a basic facial expression analysis system are fac...
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| Format: | Theses and Dissertations NonPeerReviewed |
| Published: |
[Yogyakarta] : Universitas Gadjah Mada
2010
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| Online Access: | https://repository.ugm.ac.id/87761/ http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=48625 |
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| Institution: | Universitas Gadjah Mada |
| Summary: | In daily lives, especially in interpersonal communication, face often used for
expression. Facial expressions give information about the emotional state of the
person. A facial expression is one of the behavioral characteristics. The
components of a basic facial expression analysis system are face detection, face
data extraction, and facial expression recognition. Fisherface method with
backpropagation artificial neural network approach can be used for facial
expression recognition. This method consists of two-stage process, namely PCA
and LDA. PCA is used to reduce the dimension, while the LDA is used to features
extraction of facial expressions. The system was tested with 2 databases namely
JAFFE database and MUG database. The system correctly classified the
expression in 86.85%, and false positive 25 for image type I of JAFFE, image
type II of JAFFE correctly classified the expression in 89.20% and false positive
15, meanwhile image type III of JAFFE correctly classified the expression in
87.79%, and false positive 16. The image of MUG correctly classified the
expression in 98.09%, and false positive 5. |
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