Beauty in the Eyes of Machine: A Novel Intelligent Signal Processing-Based Approach to Explain the Brain Cognition and Perception of Beauty Using Uncertainty-Based Machine Voting

The most mysterious question humans have ever attempted to answer for centuries is, “What is beauty, and how does the brain decide what beauty is?”. The main problem is that beauty is subjective, and the concept changes across cultures and generations; thus, subjective observation is necessary to derive a general conclusion. In this research, we propose a novel approach utilizing deep learning and image processing to investigate how humans perceive beauty and make decisions in a quantifiable manner. We propose a novel approach using uncertainty-based ensemble voting to determine the specific features that the brain most likely depends on to make beauty-related decisions. Furthermore, we propose a novel approach to prove the relation between golden ratio and facial beauty. The results show that beauty is more correlated with the right side of the face and specifically with the right eye. Our study and findings push boundaries between different scientific fields in addition to enabling numerous industrial applications in variant fields such as medicine and plastic surgery, cosmetics, social applications, personalized treatment, and entertainment