Automatic Personality Assessment through Movement Analysis

Area of Science:

• Psychology
• Computer Science
• Human-Computer Interaction

Background:

• Traditional personality assessments (scales, questionnaires) have limitations like lack of veracity, cultural bias, and administration constraints.
• Recent research explores using body movements as objective personality predictors.
• Developing a reliable, objective, and accessible personality assessment method is crucial across various fields.

Purpose of the Study:

• To develop and evaluate a novel system for personality assessment based on body movements.
• To address the drawbacks of conventional personality evaluation methods.
• To investigate the feasibility of using low-cost motion capture technology for personality trait identification.

Main Methods:

• A multiple linear regression model was developed to predict personality traits from movement data.
• Body movements were captured using the low-cost Microsoft Kinect camera.
• A pilot study assessed personality traits according to the Big-Five Personality Model.

Main Results:

• The system demonstrated feasibility in assessing personality through body movements.
• Extroversion and Conscientiousness were the personality traits that best fit the developed model.
• Identified specific movement patterns associated with the five personality traits.

Conclusions:

• Assessing personality through body movements is a viable alternative to traditional methods.
• The use of motion capture technology offers an objective and potentially bias-free approach to personality evaluation.
• This research opens new avenues for objective personality assessment in diverse applications.