Facial expression analysis smile photos

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Emotions are the essence of what makes us human. They impact our daily routines, our social interactions, our attention, perception, and memory. One of the strongest indicators for emotions is our face. Computer-based facial expression recognition mimics our human coding skills quite impressively as it captures raw, unfiltered emotional responses towards any type of emotionally engaging content.
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Detection of Genuine and Posed Facial Expressions of Emotion: Databases and Methods

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All Smiles : Automatic Photo Enhancement by Facial Expression Analysis – Google Research

Facial expressions of emotion play an important role in human social interactions. However, posed expressions of emotion are not always the same as genuine feelings. Recent research has found that facial expressions are increasingly used as a tool for understanding social interactions instead of personal emotions. With recent advances in computer vision and machine learning techniques, rapid progress has been made in recent years for automatic detection of genuine and posed facial expressions.
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Facial Expression Analysis: The Complete Pocket Guide

Twenty nonprofessional models were filmed while posing in three different facial expressions smile, neutral, and frown. After each pose, the models completed the PANAS questionnaire, and reported more positive affect after smiling and more negative affect after frowning. A different sample of participants evaluated the stimuli for attractiveness, arousal, clarity, genuineness, familiarity, intensity, valence, and similarity. Overall, facial expression had a main effect in all of the evaluated dimensions, with smiling models obtaining the highest ratings.
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We propose a framework for automatic enhancement of group photographs by facial expression analysis. We are motivated by the observation that group photographs are seldom perfect. Subjects may have inadvertently closed their eyes, may be looking away, or may not be smiling at that moment. Given a set of photographs of the same group of people, our algorithm uses facial analysis to determine a goodness score for each face instance in those photos.
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