Digital Design of Peking Opera Facial Makeup Based on Facial Emotion Recognition

Abstract

This study examines digital technology and cultural innovation in the context of non-genetic inheritance. Traditional digital survival approaches limit public participation and innovation dynamics. To this end, we propose an interdisciplinary approach that combines deep learning and affective computing. Specifically, we develop a CNN-based Peking Opera facial make up synthesis system to achieve intelligent deconstruction and restructuring; construct a model to match users' facial features with opera lines to generate personalised facial make up schemes; and establish a quantitative emotion assessment system using Python to achieve a dynamic correlation between expression capturing and face elements. The method enhances public interaction and broadens the influence of Peking Opera facial make up communication. The study confirms that the ‘digital empowerment + public participation’ model can promote the sustainable inheritance of intangible cultural heritage, use intelligent technology to bring users closer to traditional culture, and provide a replicable technical paradigm for the digital presentation and innovative development of traditional culture in the intelligent era.