In this book the authors discuss the recent developments in computational techniques for
automated non-invasive facial emotion detection and analysis with particular focus on the
smile. By way of applications they discuss how genuine and non-genuine smiles can be inferred
how gender is encoded in a smile and how it is possible to use the dynamics of a smile itself
as a biometric feature. It is often said that the face is a window to the soul. Bearing a
metaphor of this nature in mind one might find it intriguing to understand if any how the
physical behavioural as well as emotional characteristics of a person could be decoded from
the face itself. With the increasing deductive power of machine learning techniques it is
becoming plausible to address such questions through the development of appropriate
computational frameworks. Though there are as many as over twenty five categories of emotions
one could express regardless of the ethnicity gender or social class across humanity there
exist six common emotions - namely happiness sadness surprise fear anger and disgust - all
of which can be inferred from facial expressions. Of these facial expressions the smile is the
most prominent in social interactions. The smile bears important ramifications with beliefs
such as it makes one more attractive less stressful in upsetting situations and employers
tending to promote people who smile often. Even pockets of scientific research appear to be
forthcoming to validate such beliefs and claims e.g. the smile intensity observed in
photographs positively correlates with longevity the ability to win a fight and whether a
couple would stay married. Thus it appears that many important personality traits are encoded
in the smile itself. Therefore the deployment of computer based algorithms for studying the
human smiles in greater detail is a plausible avenue for which the authors have dedicated the
discussions in this book.
