Article

Smile intensity in photographs predicts divorce later in life

Motivation and Emotion (Impact Factor: 1.55). 33(2):99-105. DOI: 10.1007/s11031-009-9124-6

ABSTRACT Based on social–functional accounts of emotion, we conducted two studies examining whether the degree to which people smiled
in photographs predicts the likelihood of divorce. Along with other theorists, we posited that smiling behavior in photographs
is potentially indicative of underlying emotional dispositions that have direct and indirect life consequences. In the first
study, we examined participants’ positive expressive behavior in college yearbook photos and in Study 2 we examined a variety
of participants’ photos from childhood through early adulthood. In both studies, divorce was predicted by the degree to which
subjects smiled in their photos.

1 Bookmark
 · 
1,004 Views
  • Source
    Social Psychological and Personality Science. 01/2013;
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Clinicians make a variety of assessments about their clients, from judging personality traits to making diagnoses, and a variety of methods are available to do so, ranging from observations to structured interviews. A large body of work demonstrates that from a brief glimpse of another's nonverbal behavior, a variety of traits and inner states can be accurately perceived. Additionally, from these "thin slices" of behavior, even future outcomes can be predicted with some accuracy. Certain clinical disorders such as Parkinson's disease and facial paralysis disrupt nonverbal behavior and may impair clinicians' ability to make accurate judgments. In certain contexts, personality disorders, anxiety, depression, and suicide attempts and outcomes can be detected from others' nonverbal behavior. Additionally, thin slices can predict psychological adjustment to divorce, bereavement, sexual abuse, and well-being throughout life. Thus, for certain traits and disorders, judgments from a thin slice could provide a complementary tool for the clinician's toolbox. Expected final online publication date for the Annual Review of Clinical Psychology Volume 10 is March 20, 2014. Please see http://www.annualreviews.org/catalog/pubdates.aspx for revised estimates.
    Annual Review of Clinical Psychology 01/2014; · 12.42 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Both the occurrence and intensity of facial expressions are critical to what the face reveals. While much progress has been made towards the automatic detection of facial expression occurrence, controversy exists about how to estimate expression intensity. The most straight-forward approach is to train multiclass or regression models using intensity ground truth. However, collecting intensity ground truth is even more time consuming and expensive than collecting binary ground truth. As a shortcut, some researchers have proposed using the decision values of binary-trained maximum margin classifiers as a proxy for expression intensity. We provide empirical evidence that this heuristic is flawed in practice as well as in theory. Unfortunately, there are no shortcuts when it comes to estimating smile intensity: researchers must take the time to collect and train on intensity ground truth. However, if they do so, high reliability with expert human coders can be achieved. Intensity-trained multiclass and regression models outperformed binary-trained classifier decision values on smile intensity estimation across multiple databases and methods for feature extraction and dimensionality reduction. Multiclass models even outperformed binary-trained classifiers on smile occurrence detection.
    Pattern Recognition Letters 10/2014; · 1.27 Impact Factor

Full-text (2 Sources)

View
1,799 Downloads
Available from
May 22, 2014