Exploring Facial Differences in European Countries Boundary by Fine-Tuned Neural Networks

Abstract

Travel Agents and retailers are always curious about where their customers come from, as this would help them increase their sale and optimize their marketing models. In this study, we build a system to predict where people come from in Europe by analyzing their faces. The countries that have been chosen for the study are Russia, Italy, Germany, Spain, and France. In the first stage of the study, we implement different neural network classifiers on the dataset of people's faces that we collected from Twitter. The highest accuracy achieved is 53.2%, while human accuracy is only 26.96%. In the second stage of the study, we analyze 11 different facial features that might differentiate people in those five countries. The study lays the groundwork for future work to find out differences/similarities of people's faces around the world regardless of their current geographic location.