“What others call ultra-quality, we call normal. What we call high quality, the others call impossible.”
Learn how to use the powerful photogrammetry software RealityCapture from CapturingReality and get started with 3D modeling! With us you will learn how to create highly accurate point clouds, orthoprojections, terrain- and 3D models with your camera, drone and/or laser scanner.
RealityCapture is a photogrammetry software which is capable of producing extremely high-resolution, photorealistic 3D models that can be generated from photo and laserscan data. It works with terrestrial close-up imagery (DSLR), aerial imagery (UAV & aircraft) and static laserscan data.
The advantage of the software is it’s speed and the low hardware requirements – the program does not necessarily need a workstation. It already runs on a standard laptop (i5/i7, min. 8GB Ram & 1GB GPU, 64-bit system). The software is mainly used in the gaming industry, architecture and archeology, but also in surveying.
We have been using RealityCapture for over 8 years in various surveying and visualisation projects. As the first and largest provider of RealityCapture trainings in Germany we are happy to share our experience and workflows with our customers. Our certified photogrammetry experts will lead you through the complete workflow from data acquisition over processing to the finished product.
In addition to RealityCapture, our training courses introduce you to open source software for processing point clouds, polygon meshes, textures and orthophotos. Also we show you how to further refine your photogrammetry products.
We offer individual or group training for RealityCapture, online & offline – either at your site or at our office in Aachen/D, tailored to your needs.
Requirements for participation is your own workstation and a current RealityCapture license (PPI or demo license). We can provide workstations with adequate hardware for the training on request.
Agenda RealityCapture Training:
- Data aquisition techniques for RealityCapture Projects (UAV, DSLR/DSLM & Laserscanner)
- Joint data acquisition for a first project (UAV, DSLR/DSLM & Laserscanner)
- Registration and cleaning of laserscan data in PinPoint (Leica/FARO)
- Introduction to the RealityCapture GUI
- RealityCapture Workflow
- General settings & properties in RC
- Data import
- Alignment process in RealityCapture
- Misalignment Detection Tool
- Reconstruction process in RealityCapture
- Import of Laserscan-data (.ptx/.e57) and alignment with images
- Control points, marker and distances in RC
- Control Points and component-workflow
- Working with referenced image data (RTK)
- Import laserscans and align with images
- Reconstructing the pointcloud & mesh (only photo, only laserscan and combination of both)
- Refine and simplify meshes
- Texturing and colorizing in RealityCapture
- texture reprojection
- Orthoprojections in RC
- Image Mosaicking Workflow
- Orthomosaic editing
- Generating digital elevation models
- Volume calculations
- Profiles & contour lines
- Cross section tool
- Color correction in RealityCapture
- Working with image-layers
- Working with masks in RealityCapture
- Renderings and animations in RealityCapture
- Batchprocessing using CLI (Command Line interface)
- Real-Time Assistant
- Export data in various file formats
- Export for UnrealEngine / Sketchfab / CesiumIon / NIRA / Potree / ArcGIS Pro / Twinmotion / Twinspect
- External opensource software for further pointcloud / mesh processing (CloudCompare / Meshlab)
- 64bit machine with at least 8GB of RAM
- 64bit Microsoft Windows version 7 / 8 / 8.1 / 10 or Windows Server version 2008+
- NVIDIA graphics card with CUDA 3.0+ capabilities and 1GB VRAM
- CUDA Toolkit 10.2, minimal driver version 441.22.
We recommend using a machine with at least 4 CPU cores, 16GB of RAM and 1024 CUDA cores. If you do not have the NVIDIA card, you will be still able to run the application and register images, you will not be able to create a textured mesh.
Please contact us for further information on the training and pricing: email@example.com
Mit freundlicher Unterstützung von CapturingReality