Facial Expression Recognition Using Self Organizing Map

Facial expression recognition has attracted a significant interest in the scientific community, as it plays a vital role in human centered interfaces. Many applications require efficient facial expression recognition in order to achieve desired results. In this paper facial expression recognition is presented using self organizing map(SOM). At first placement of Candide grid nodes to face landmarks of the image is carried out. For the face recognition system Gabor filters extract the feature vector values. These values are used for classification and clustering in the SOM grid. The system adapts to the user´s preferences by returning more relevant images from the SOM grid for which the responses have been most densely mapped. The main contribution of this work is the identification of a face image from a database along with its gesture. Results obtained on the test image database indicate that the system retrieves the relevant expressions accurately with minimum number of training steps.