Smiling Faces Are Better for Face Recognition

This challenges the common notion of using neutral face images for face recognition. As smile is the most common expression, it can be used for optimizing performance when tens of thousands or even million faces are to be recognized. 

To test this, Yakoob and Davis, from University of Maryland, conducted an experiment in two parts. Two databases containing neutral and smiling face images of same person in each database were used. For first part of experiment, 10 subjects from first database were used. The discrimination power was calculated for smiling and neutral faces. 

It was found that the discrimination power was more for smiling expression than for neutral expressions which showed that smiling faces are better in face recognition.

In second part of the experiment, more face images were added from second database. In first stage of second part, 0-15 faces were added. Then in second stage, 0-40 faces were added again. The average discriminating power was calculated. 

In both stages, the average discriminating power of smiling faces was more than the average discriminating power of neutral faces which again showed that smiling faces are better for face recognition. 

To detect a face of person in video clips, expressive faces such as smiles will be more cooperative for access applications as well as surveillance purposes.

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Reference – Yaser Yakoob and Larry Davis. Computer Vision Laboratory, University of Maryland, College Park, MD 20472. Research paper name - Smiling Faces Are Better for Face Recognition. Published In - Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition (2002).

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