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Physiognomy: Personality Traits Prediction by Learning 被引量:1
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作者 Ting Zhang Ri-Zhen Qin +3 位作者 Qiu-Lei Dong Wei Gao hua-rong xu Zhan-Yi Hu 《International Journal of Automation and computing》 EI CSCD 2017年第4期386-395,共10页
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 possibl... 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. 展开更多
关键词 Personality traits PHYSIOGNOMY face image deep learning convolutional neural network (CNN).
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