Physiognomy： Personality Traits Prediction by Learning

作     者：Ting Zhang Ri-Zhen Qin Qiu-Lei Dong Wei Gao Hua-Rong Xu Zhan-Yi Hu 

作者机构：National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing 100190 China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Beijing 100190 Chins University of Chinese Academy of Sciences Beijing 100049 China Department of Computer Science &: Technology Xiamen Institute of Technology Xiamen 361024 China 

出 版 物：《International Journal of Automation and computing》 (国际自动化与计算杂志（英文版）)

年 卷 期：2017年第14卷第4期

页      面：386-395页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 080203[工学-机械设计及理论] 0835[工学-软件工程] 0802[工学-机械工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by National Natural Science Foundation of China(Nos.61333015,61421004 and 61375042) Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDB02070002) 

主　　题：Personality traits physiognomy face image deep learning convolutional neural network (CNN). 

摘      要：Evaluating individuals＇ personality traits and intelligence from their faces plays a crucial role in interpersonal relationship and important social events such as elections and court sentences. To assess the possible correlations between personality traits （also measured intelligence） and face images, we first construct a dataset consisting of face photographs, personality measurements, and intelligence measurements. Then, we build an end-to-end convolutional neural network for prediction of personality traits and intelligence to investigate whether self-reported personality traits and intelligence can be predicted reliably from a face image. To our knowledge, it is the first work where deep learning is applied to this problem. Experimental results show the following three points： 1） ＂Rule-consciousness＂ and ＂Tension＂ can be reliably predicted from face images. 2） It is difficult, if not impossible, to predict intelligence from face images, a finding in accord with previous studies. 3） Convolutional neural network （CNN） features outperform traditional handcrafted features in predicting traits.