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Nanite Tessellation Explored for Dynamic Mesh Displacement in Unreal Engine
Key points
- Nanite Tessellation dynamically tessellates and displaces meshes.
- Displacement is controlled by shader graphs in UE's material editor.
- It addresses geometry amplification alongside existing Nanite features.
- The system prioritizes data compression for specific geometry needs.
What is Nanite Tessellation?
Nanite Tessellation is a system designed for dynamically tessellating meshes and applying displacement. The displacement effects are generated from a shader graph, which can be authored directly within Unreal Engine's material editor. This functionality extends the capabilities already provided by Nanite, focusing on adding detail through dynamic geometry modification.
Why Geometry Amplification?
The need for geometry amplification, even with Nanite's existing virtualization capabilities, stems from specific challenges. While Nanite offers a general-purpose solution for virtualized geometry by simplifying complex meshes, it can be resource-intensive to store full topology and attributes for every point on a surface. Nanite Tessellation provides an alternative for cases where amplification is more efficient than full simplification.
Data Compression Advantages
A key benefit of Nanite Tessellation is its efficiency in data compression. Scalar displacement fields, whether artist-authored maps or derived from projecting detailed surfaces onto simpler ones, require significantly less data storage compared to full 3D point data with complete attributes. This approach leverages well-understood techniques for compressing regular 2D data, such as images, which are more efficient than storing complex mesh topology.
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Reporting from
A new system called Nanite Tessellation is being developed to dynamically tessellate and displace meshes using shader graphs within Unreal Engine's material editor. This approach complements existing Nanite technology by offering a more efficient way to handle geometry amplification for specific use cases, particularly where data compression is critical.