There is no abstract available for this article.
This work was supported by Strategic Priority Research Program of the CAS (Grant No. XDB02070002) and National Natural Science Foundation of China (Grant Nos. 61421004, 61333015).
[1] Ballew C C, Todorov A. Predicting political elections from rapid and unreflective face judgments. Proc Natl Acad Sci USA, 2007, 104: 17948-17953 CrossRef PubMed ADS Google Scholar
[2] Oosterhof N N, Todorov A. The functional basis of face evaluation. Proc Natl Acad Sci USA, 2008, 105: 11087-11092 CrossRef PubMed ADS Google Scholar
[3] Carney D R, Colvin C R, Hall J A. A thin slice perspective on the accuracy of first impressions. J Res Personality, 2007, 41: 1054-1072 CrossRef Google Scholar
[4] Wolffhechel K, Fagertun J, Jacobsen U P, et al. Interpretation of appearance: the effect of facial features on first impressions and personality. Plos One, 2014, 9: 127--140. Google Scholar
[5] Perceived Intelligence Is Associated with Measured Intelligence in Men but Not Women. PLoS ONE, 2014, 9: e81237 CrossRef PubMed ADS Google Scholar
[6] Rojas M, Masip D, Todorov A, et al. Automatic prediction of facial trait judgments: appearance vs. structural models. Plos One, 2011, 6: 1--12. Google Scholar
[7] Qin R Z. Predicting personality traits from the human face (in Chinese). Dissertation for Master's Degree. Beijing: University of Chinese Academy of Sciences, 2016. Google Scholar
Gender | Male | Female | ||||||
feature | Classification | Dim. | Regression | Dim. | Classification | Dim. | Regression | Dim. |
Parzen ($\surd$) | 30 | Linear | 2 | Parzen ($\surd$) | 30 | Linear | 2 | |
DTree | 30 | Ridge | 2 | DTree | 15 | Ridge | 2 | |
Structural | KNN | 20 | Lasso | 2 | KNN | 30 | Lasso | 2 |
NaiveB | 5 | Pinv | 2 | NavieB | 30 | Pinv | 2 | |
RF | 20 | KNN | 2 | RF | 20 | KNN | 10 | |
SVM ($\surd$) | 5 | SVM ($\surd$) | 5 | |||||
Parzen ($\surd$) | 5 | Linear | 2 | Parzen ($\surd$) | 15 | Linear | 2 | |
DTree | 20 | Ridge | 2 | DTree | 5 | Ridge | 2 | |
Appearance | KNN | 10 | Lasso | 20 | KNN | 10 | Lasso ($\surd$) | 15 |
NaiveB | 5 | Pinv | 2 | NavieB | 5 | Pinv | 2 | |
RF | 20 | KNN | 30 | RF | 30 | KNN | 2 | |
SVM ($\surd$) | 5 | SVM | 20 |