3D Face Modeling base on the Efficient Detecting of Facial Feature Parts
Hiroki Tezuka, Takashi Miyazaki · 2018
Various kind of 3D model tools for creating are required for 3D printers popular rapidly in recent years. In particular, 3D CG software is used when creating a 3D model of a complicated object such as a person, but it takes time to create that details. There is a method of extracting feature points and performing simulation in the conventional 3D model creation method, but we need a device with high performance for simulation(1-3) . In recent years, there are methods using deep learning. However, in order to improve accuracy, it is necessary to learn a large amount of data. In this paper, we propose a method to create a 3D model of a human face briefly without using high-performance equipment and deep learning, and actually create the 3D model. In addition, we propose a method to measure automatically data necessary for creating a 3D face model using image prosessing such as cascade classifiers of Haarlike feature, extraction of hue component in HSV color space for extracting hair and skin color, and edge detection. Finally, we investigated the error on the measurement results of the face images by the proposed method.