Physiognomy： Personality Traits Prediction by Learning  

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

机构地区：[1]National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China [2]Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Beijing 100190, Chins [3]University of Chinese Academy of Sciences, Beijing 100049, China [4]Department of Computer Science &: Technology, Xiamen Institute of Technology, Xiamen 361024, China

出　　处：《International Journal of Automation and computing》2017年第4期386-395,共10页国际自动化与计算杂志（英文版）

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)

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.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.

关 键 词：Personality traits PHYSIOGNOMY face image deep learning convolutional neural network （CNN）. 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] TP391.41[自动化与计算机技术—控制科学与工程]