Predicting Personality based on Self-Introduction Video

• Published in: IFAC-PapersOnLine Vol. 53; no. 5; pp. 452 - 457
• Main Authors: Yeye, Wen, Deyuan, Chen, Baobin, Li, Xiaoyang, Wang, Xiaoqian, Liu, Tingshao, Zhu
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 2020
• Subjects: Facial video; Machine learning; Personality prediction; Self-introduction video; Self-introduction video; Facial video; Machine learning; Personality prediction
• ISSN: 2405-8963; 2405-8963
• DOI: 10.1016/j.ifacol.2021.04.217

Personality affects individual’s work and life style, and has important guiding significance for individual’s psychological counseling and career development. Traditionally, researchers use scales to measure personality. However, in the psychological assessment of job hunting and enrollment, it can’t rule out the possibility of answer deceptively under the influence of social desirability. In recent years, with the development of machine learning, new techniques have been developed for personality recognition. This paper uses participants’ self-introduction videos and Big Five personality scale scores to train five-dimensional personality prediction model by key point recording, feature extraction and dimensionality reduction, modeling, and iterative tuning. The results show that the prediction scores of the personality model based on the self-introduction video is close to or achieved medium correlation with scores of questionnaires in all dimensions (r=0.32~0.44, p<0.05). It can provide non-intrusive automatic personality recognition, which indicates a new way of personality measurement.