Annotation

The course will focus on 3D scene creation and visualization using open-source Blender 3.3 LTS. We will start by demonstrating the basics and features of Blender. We will go through the fundamentals of Geometry Nodes in Blender before concentrating on procedural modeling with Geometry Nodes to create various 3D scenes (such as generating a valley with houses, roads, and vegetation or even generating some scientific elements). We will introduce our developed plug-in to render the finished scene on the HPC cluster. As part of the program, we will also demonstrate how to use Blender's Shader Editor and an AI tool using which you can create photo-realistic imaginative textures. We will show how to create your add-on during the course. Within the course, we will also work with an example of volumetric data, manipulate voxels, visualize the data, and turn it into actual geometry.

Benefits for the attendees, and what they will learn:

Participants will gain knowledge on procedurally creating 3D scenes, rendering scenes on clusters, creating textures using AI tools, and visualizing volumetric data. The course will be mainly hands-on.

Level

45% beginner, 55% intermediate

Language

English

Prerequisites

Basic knowledge of navigating in Blender and basic familiarity with Python programming will be helpful, though not mandatory.

Participants must bring their laptops and mouse. The full-sized keyboard is highly beneficial in Blender, some USB keyboards will be available for in-person attendees.

Tutors

Khyati Sethia (M.S., Data Science) graduated from the University of Salford in 2019. Khyati is currently a researcher in the Infrastructure Research Lab at the IT4Innovations National Supercomputing Center, Czech Republic. Khyati began using Blender while working on a project involving a train simulator for obstacle detection, and she intends to utilize it for other creative projects involving the 3D model generation and visualization. She plans to focus on using machine learning in the research areas of medical imaging, image processing, and using artificial intelligence in Blender.

Petr Strakoš obtained his Ph.D. in Mechanical Engineering from the Czech Technical University in Prague. Now he is a member of the Infrastructure Research Lab and the VaVR (Visualization and Virtual Reality) group, where he focuses on research in visualization, image processing, and efficient utilization of these topics on a cluster. He also cooperates with partners from industry and other institutions in applied research.

Acknowledgments

This event was supported by the EuroCC project. This project has received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement No 951732. The JU receives support from the European Union’s Horizon 2020 research and innovation program and Germany, Bulgaria, Austria, Croatia, Cyprus, the Czech Republic, Denmark, Estonia, Finland, Greece, Hungary, Ireland, Italy, Lithuania, Latvia, Poland, Portugal, Romania, Slovenia, Spain, Sweden, the United Kingdom, France, the Netherlands, Belgium, Luxembourg, Slovakia, Norway, Switzerland, Turkey, Republic of North Macedonia, Iceland, Montenegro. This project has received funding from the Ministry of Education, Youth and Sports of the Czech Republic (ID: MC2101).