Methods and Algorithms for Visualizing the Volumetric Model of an Object Based on its Visible Part

The research focuses on the use of computer vision and machine learning methods to determine the central axis of symmetry of the object, as well as on the application of various approaches to generate the necessary additions. Special attention is paid to processing images with partially visible objects and improving the accuracy of their restored parts through adaptive algorithms. The presented work demonstrates the convenience and effectiveness of the proposed methods in various scenarios, including the reconstruction of architectural elements, natural objects, and complex artificial structures in comparison with calculations based on the full set of images. The provided examples and experimental data show that the developed approaches can be successfully applied in physics, engineering, and computer vision to solve tasks related to restoring objects from their partial images.