Neuro Fuzzy Model for Human Face Expression Recognition

Burange, Mayur S.

doi:10.9790/0661-0120106

Cited by 1 publication

(1 citation statement)

References 2 publications

(2 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Viola -Jones algorithm is discussed with its importance for face detection and face parts. Rule based classification [3]; PCA [4] with fuzzy [5] C-means clustering and feed forward back propagation neural network is used as a classifier for classifying the expressions of supplied face into four basic categories like neutral, surprise, sad and happy. For face portion segmentation basic image processing operation like projection and skin colour polynomial model [6] are used.…”

Section: Introductionmentioning

confidence: 99%

Effective face detection, feature extraction & neural network based approaches for facial expression recognition

Muttu

Virani

2015

2015 International Conference on Information Processing (ICIP)

View full text Add to dashboard Cite

Face expression recognition is a typical task to make human and machine interaction possible. Besides this, medical science and other applications demand for such system. This paper focusses on importance of face detection and its feature parts. For this, Viola -Jones algorithm was implemented. The crucial part of this paper is feature extraction and the algorithm used for the purpose is modified local binary patterns algorithm. The results of feature extraction algorithms are compared to that in the literature to show the limitations of the existing algorithms and their suitabilility for this application. Neural network based approaches are used for classification of facial expressions. This paper enumerates two classification techniques for the facial expressions. The system performs well by the method used by us and gives efficient results. This was experimented using the Taiwanian database and the Japanese database.

show abstract

Section: Introductionmentioning

confidence: 99%