Personality Traits Estimation Based on Job Interview Video Analysis: Importance of Human Nonverbal Cues Detection

Abstract

In this research, we delve into the analysis of non-verbal cues and their impact on evaluating job performance estimation and hireability by analyzing video interviews. We study a variety of non-verbal cues, which can be extracted from video interviews and can provide a framework that utilizes the extracted features, and we combine them with personality traits to estimate sales abilities. Experimenting on the (Human Face Video Dataset for Personality Traits Detection) VPTD dataset, we proved the importance of smiling as a valid indicator for estimating extraversion and sales abilities. We also examined the role of head movements (represented by the rotation angles, roll, pitch, and yaw) since they play a crucial role in evaluating personality traits in general and extraversion and neuroticism in particular. The testing results show how these non-verbal cues can be used as assisting features in the proposed approach to provide a valid, reliable, and accurate estimation of sales abilities and job performance.

Keywords

• OCEAN model
• personality traits
• non-verbal cues
• head movements