Evaluating Effectiveness of Using Multi-Features to Differentiate Real from Fake Facial Images

Face analysis is one of the key research areas in the field of computer vision with applications in numerous areas. Face recognition, emotion recognition, and more recently deepfake detection have greatly benefited from the advancements in the field of face analysis. Our research attempts to identify useful facial features for analysis. We first analyze the effectiveness of geometric facial features for the purpose of emotion recognition. In later experiments, a fusion scheme was created based on the preliminary analysis,which tested the performance of these selected features for the identification of real and fake images. We include local image features in combination with geometric facial features to measure their effectiveness in fake image detection tasks. The promising results produced in this study can be used to perform a more in-depth analysis of face geometry and its result in facial analysis.