Gesture Recognition in Mock Interviews for Placements Using Machine Learning

Gestures have a vital role in the selection procedure of an interview. Kinesics, which includes expressions of the face, hands, head, eyes, body posture, and appearance of the candidate, is a vital parameter for a job interview. To keep this view in mind, the researchers in this paper have explored and identified the positive and negative gestures that are essential for a candidate to know before appearing in an interview. The researchers in this study employed machine learning technology that can be utilized to understand human conduct during mock interview sessions in universities and colleges for students preparing for placement in alleged companies. It relates to the recognition of expressions of motion involving the movement of hands, face, eyes, and head. The researchers in the present paper have employed different machine-learning techniques like “Random Forest”, “Neural Network”, “Logistic Regression”, and “AdaBoost” to measure human behavior in the framework of placement discussions.