Paper Title
Multi-View Facial Expression Recognition Based on Local Binary Patterns: Data Handling and Data Classification

Facial expression recognition is an active research field in the application development sector which includes animation, sociable robots and neuro-marketing. Facial Expression recognition is not simple, because the layers of images can vary due to the mode of expression, background, pose and brightness. Analysis of Automatic facial expression recognition is a challenging problem and it is very significant application in many research areas like data driven animation and human computer interaction. In this article, we examine the facial representation depends on the Local Binary Patterns. To minimize the issue, preprocessing methodologies were used to extract only the expression of particular attributes from the facial images and explore the presentation order of samples at the training sample order. The proposed method attains better results when compared to the existing techniques and achieves 97% accuracy. Keywords – Animation, Brightness, Neuro-Marketing, Binary Patterns