Smiling faces are better for face recognition

This paper investigates face recognition during facial expressions. While face expressions have been treated as an adverse factor in standard face recognition approaches, our research suggests that, if a system has a choice in the selection of faces to use in training and recognition, its best performance would be obtained on faces displaying expressions. Naturally, smiling faces are the most prevalent (among expressive faces) for both training and recognition in dynamic scenarios. We employ a measure of discrimination power that is computed from between-class and within-class scatter matrices. Two databases are used to show the performance differences on different sets of faces.