Modern Physiognomy: An Investigation on Predicting Personality Traits and Intelligence from the Human Face
Rizhen Qin, Wei Gao, Huarong Xu, Zhanyi Hu

TL;DR
This study investigates the potential of predicting personality traits and intelligence from facial images using machine learning, finding some traits can be reliably classified but overall prediction of scores remains challenging.
Contribution
It introduces a combined facial structural and appearance feature approach for trait prediction and explores the predictability of personality and intelligence from faces and fingerprints.
Findings
Rule-consciousness and Vigilance can be reliably predicted
Female facial traits are predicted more accurately than males
Predicting intelligence from facial features is difficult
Abstract
The human behavior of evaluating other individuals with respect to their personality traits and intelligence by evaluating their faces plays a crucial role in human relations. These trait judgments might influence important social outcomes in our lives such as elections and court sentences. Previous studies have reported that human can make valid inferences for at least four personality traits. In addition, some studies have demonstrated that facial trait evaluation can be learned using machine learning methods accurately. In this work, we experimentally explore whether self-reported personality traits and intelligence can be predicted reliably from a facial image. More specifically, the prediction problem is separately cast in two parts: a classification task and a regression task. A facial structural feature is constructed from the relations among facial salient points, and an…
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Taxonomy
TopicsEvolutionary Psychology and Human Behavior · Face recognition and analysis · Face and Expression Recognition
