동물 캐릭터 적합 배우 추천 알고리즘 연구

Abstract

This study designed a virtual casting system that can be incorporated into the film industry. Through CNN deep learning and PCA region extraction we obtain face standard data for each animal and store similarity and region vector values in DB. We also leverage two similarity measurements to enable users to accurately provide the desired information. When the user chooses an animal of a character to be implemented in due diligence the recommender system utilizes the existing analyzed DB to provide standardized animal images. This allows users to recommend and cast actors who are most similar to the image of an implemented animal. This work is meaningful in showing that the results of existing studies can be utilized industrially.