Novel Framework for Job Interview Processing Automation Based on Intelligent Video Processing

In this research, we introduce a novel framework for assessing participants’ abilities and job performance through analyzing personality traits and nonverbal cues. We introduce a comprehensive analysis of the correlation between nonverbal features and job performance, shedding light on the most nonverbal cues noticed by the interviewers through the job interviews and how these cues affect the hiring decision. The proposed framework analyzes video interviews to estimate personality traits (openness, conscientiousness, extraversion, agreeableness, and neuroticism) and nonverbal features (eye gaze, facial landmarks, head movements, smiling, posture, speech, and etc.). The knowledge base utilizes the extracted features to assess job performance and sales abilities. We implemented the framework and detected smiling through the video analysis using VPTD dataset. The findings show a significant moderate correlation based on Spearman’s correlation coefficient (p_value less than 0,05) with extraversion and self-estimated abilities to work in sales.