Analysis of Emotional Authenticity Displayed by Film Actors Using Image Processing Techniques

Abstract

This study analyzes a social phenomenon using technical methods to uncover the underlying reasons for the researched phenomenon. This study investigates the authenticity of facial expressions and emotional cues of well-known film actors in Turkish comedy cinema films. For the study, 480 video data samples related to the actors were collected from the social media platform YouTube. The videos were categorized into smile, surprise, and anger, with 120 samples analyzed for each category. The Kaggle database containing facial expressions of smile, surprise, and anger from regular individuals was utilized to compare the images. The Local Binary Pattern (LBP) feature extraction technique was employed to extract features from the images. Machine learning models were then constructed using the extracted features. Based on the classification results, the accuracy values were 99.37% for the smile category, 97.19% for the surprise category, and 97.81% for the anger category. The analysis results show that the emotional expressions of film actors and normal individuals differ. This study aims to develop a unique perspective by highlighting the distinctive characteristics of renowned actors through their emotional expressions.

Keywords

• Image Processing Techniques
• Local Binary Patterns
• LBP
• Feature Extraction
• Cinema
• Film Actor
• Emotional Authenticity
• Facial Expressions

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