Helsinki, Finland (September 30, 2020) - With the advent of the next generation consoles, Umbra is glad to announce that its Visibility SDK will support the Microsoft’s new family of Xbox consoles - the Xbox Series X and Xbox Series S.
The SceneStream customer portal has been in somewhat of a need to be redesigned for a while now. Luckily, today is the day we finally get to show what we've been working on. Welcome to the beta of the redesigned portal at https://beta.umbra.io.
Not long ago, we wrote about how you can use Umbra SceneStream to render large and complex 3D models in Unity. This time around we thought it would be a nice tidbit to showcase some of the lesser known features that our Unity SDK supports.
With the recent release of DOOM Eternal, we dug into our blog archives to resurrect this absolute gem posted in May 2016 from our very own, the one and only, resident ass-hat, DPO, Murkku - the Cloud Anarchist who spends the next 10 minutes remininiscing how the spawns of Hell will once again get their ass kicked.
One of the biggest issues our customers and partners encounter is the sheer amount of time it takes to import large 3D models into game engines - let alone optimizing them for smooth runtime performance. Umbra SceneStream is designed to solve this particular case.
Meshes to us are like paintings to an artist: never good enough and always with room for improvement. And improve them is exactly what we’ve done with this latest release. Hot off the software printing press, here’s a list of latest feature additions to Umbra’s platform.
Laser scanning produces exceptionally detailed 3D point clouds of real-world locations, but there are often lots of missing areas that the scanner didn't see. Is it possible to bring them back somehow?
In computer graphics, there are multiple different ways to represent 3D geometry. Basically, these can be broken down to three different groups: volumetric representations with a set of polyhedrons, surface representations with a set of polygons and point clouds with a set of points.
A while ago, I wrote about a scalable pipeline for processing point clouds. While the text gave an overview of what such a pipeline might look like, it was quite abstract. This time, instead of hand-waving on a very high level, I’m going to present some actual results.