A method for converting a smiling face to a neutral face with applications to face recognition

The human face displays a variety of expressions, like smile, sorrow, surprise, etc. All these expressions constitute nonrigid motions of various features of the face. These expressions lead to a significant change in the appearance of a facial image which leads to a drop in the recognition accuracy of a face-recognition system trained with neutral faces. There are other factors like pose and illumination which also lead to performance drops. Researchers have proposed methods to tackle the effects of pose and illumination; however, there has been little work on how to tackle expressions. We attempt to address the issue of expression invariant face-recognition. We present preprocessing steps for converting a smiling face to a neutral face. We expect that this would in turn make the vector in the feature space to be closer to the correct vector in the gallery, in an appearance-based face recognition. This conjecture is supported by our recognition results which demonstrate that the accuracy goes up if we include the expression-normalization block.