Material Segmentation uses a neural network to automate masking, enabling Artists to separate textures from scans or images. A huge time saver, and just one of the brilliant modules in ArtEngine.
Scanning the real world provides great richness and variety to the asset library, however scan-based workflows also mean there is unfortunate amount of preparation needed to use these scans. Artists are required to spend a lot of time masking images to highlight the exact, individual components they require.
The Texture Segmentation module automates the masking process with a neural network based solution that automatically identifies and masks out the different homogeneous textures that exist in a heterogeneous scan or natural image. This module fully automates what is traditionally a slow and highly manual task for Artists.
APPLICATIONS OF TEXTURE SEGMENTATION
This module within ArtEngine automates the masking process with a neural network based solution that automatically identifies and masks out the different homogeneous textures, and generates outputs from each.
Texture Segmentation Use Case
Use Case: Automating workflows.
Time saved: 45 minutes per material.
A game studio that has decided to go down the photogrammetry route with their latest game may have a preliminary asset gathering stage in which the team goes and captures lots of different scans that will be applicable to their game. Once scanned those artists would have to process them by hand. Using ArtEngine from Artomatix, they can apply their scans to Texture Segmentation and gain automatic masks to separate the textures out.
The Texture Segmentation module in ArtEngine uses a neural network to recognise and separate out different textures from within a scan. It will automatically draw masks over these areas which means that an artist can feed a complicated scan into the node and split it up into its constituent parts.
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