3D face model reconstructing from its 2D images using neural networks
Oleksandra Aleksandrova, Yevgen Bashkov · 2019 IEEE International Conference on Advanced Trends in Information Theory (ATIT) · 2019
The most common methods for reconstruction of 3D face models are considered, their quantitative estimates are analyzed and determined, the most promising approach - 3D Morphable Model is highlighted. The necessity of its modification is substantiated in order to improve the results of reconstruction based on the analysis of the main components and the use of a neural network. One of the advantages of using the 3D Morphable Model with the analysis of the main components is the representation of only a probable solution, when the space of solutions is limited, thereby simplifying the problem being solved. While the original approach involves manual initialization. The main result, is an approach for creating three-dimensional face models from their 2D images, having least time and satisfactory root mean square error. The tasks of further research are determined.