Improving facial attraction in videos

Abstract

The face plays an important role both socially and culturally and has been extensively studied especially in investigations on perception. It is accepted that an attractive face tends to draw and keep the attention of the observer for a longer time. Drawing and keeping the attention is an important issue that can be beneficial in a variety of applications, including advertising, journalism, and education. In this article, we present a fully automated process to improve the attractiveness of faces in images and video. Our approach automatically identifies points of interest on the face and measures the distances between them, fusing the use of classifiers searches the database of reference face images deemed to be attractive to identify the pattern of points of interest more adequate to improve the attractiveness. The modified points of interest are projected in real-time onto a three-dimensional face mesh to support the consistent transformation of the face in a video sequence. In addition to the geometric transformation, texture is also automatically smoothed through a smoothing mask and weighted sum of textures. The process as a whole enables the improving of attractiveness not only in images but also in videos in real time.