Development of an Adaptive Module for Visualization of the Surrounding Space for Cloud Educational Environment

Abstract

The article considers the most popular methods of landscape map generation, identifies the key advantages and disadvantages of each approach, both individually and in its entirety. The object of this study was the combined Voronoi diagram method and diamond-square algorithm. The procedure of recognition of objects from real photographs of landscape for the application of theoretical knowledge and practical work of students of technical specialties of the University. At the heart of the study identified the key stages that accompany the processing and visualization of the image, their parameters and required functions. The article presents screenshots of real photos and visualized three-dimensional scene. In addition, the advantages of using big data technologies on the example of the developed technology of environment visualization are revealed. The system is adapted for the cloud educational platform, through which it is possible to study individually and differentially in the context of the massive open online course the possibilities of a real and key for the industry landscape area. The following are ways to improve the performance of the existing visualization subsystem by using the display of multiple objects of the same type, which is based on the serial transition and cloning of one node of the model to another. The data array containing the coordinates of the location for an object in which changes occur in accordance with the real photo, and arrays of normal and texture coordinates are copied without changes.