Analysis of Facial Expression using LBP and Artificial Neural Network
Renuka R. Londhe, Vrushsen P. Pawar · International Journal of Computer Applications · 2012
Facial Expression Recognition is rapidly becoming area of interest in computer science and human computer interaction. The most expressive way of displaying the emotions by human is through the facial expressions. Local Binary Patterns are widely used for texture classification. In this research paper, we have projected a method for facial expression recognition using Local Binary Patterns (LBP) as features and Artificial Neural Network as a classification tool and we developed associated scheme. The six universal expressions i. e. anger, Generalized Feed-forward Neural Network recognizes disgust, fear, happy, sad, and surprise as well as seventh one neutral. The Neural Network trained and tested by using Levenberg Marquart (LM) nonlinear optimization algorithm. We are able to attain 93. 3 % classification rate with testing performance 0. 0573.