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Comparative Study of Facial Feature Extraction, Expressions and Emotion Recognition


Affiliations
1 School of Comutational Sciences, Solapur University, Solapur (M.S), India
2 School of Technology, S.R.T.M.U.N. Sub- campus, Latur, (M.S), India
 

Facial recognition is one of the most relevant applications of image analysis. It is a true challenge to build an automated system which equals human ability to recognize faces. Facial Recognition is an unsolved problem and a demanded technology. The challenges for Facial Recognition extract of facial features, expression and emotions. In this paper we have study the facial extraction approaches, facial expressions and emotion recognition. By studding different approaches and attempt can be made to develop hybrid approach for facial feature extraction and recognition accuracy can be further improved using Artificial Neural Network approach and hybrid approach such ANFIS. By studying various methods we may have conclude that PCA with SVD is superior to PCA in terms of recognition rate for basic emotions.

Keywords

Feature Extraction, Facial Expression, Face Recognition, Image Processing, PCA
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Abstract Views: 326

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  • Comparative Study of Facial Feature Extraction, Expressions and Emotion Recognition

Abstract Views: 326  |  PDF Views: 339

Authors

Shinde A. R.
School of Comutational Sciences, Solapur University, Solapur (M.S), India
Agnihotri P. P.
School of Technology, S.R.T.M.U.N. Sub- campus, Latur, (M.S), India

Abstract


Facial recognition is one of the most relevant applications of image analysis. It is a true challenge to build an automated system which equals human ability to recognize faces. Facial Recognition is an unsolved problem and a demanded technology. The challenges for Facial Recognition extract of facial features, expression and emotions. In this paper we have study the facial extraction approaches, facial expressions and emotion recognition. By studding different approaches and attempt can be made to develop hybrid approach for facial feature extraction and recognition accuracy can be further improved using Artificial Neural Network approach and hybrid approach such ANFIS. By studying various methods we may have conclude that PCA with SVD is superior to PCA in terms of recognition rate for basic emotions.

Keywords


Feature Extraction, Facial Expression, Face Recognition, Image Processing, PCA