Stunad Spatial

Stunad Spatial is a research-driven exploration focused on treating point cloud data as a primary design and computation medium rather than merely an intermediate step toward mesh generation.

The project investigates how raw spatial scans can be structured, filtered, and manipulated in real time to support interactive design tools and spatial computing workflows.

• Large-scale point clouds
• Spatial data structuring
• Performance optimization
• Real-time interaction
• XR System Integration

Instead of immediately converting point clouds into meshes, the project treats point data as first-class geometry. Operations such as filtering, clustering, sampling, and spatial querying are performed directly on the point data, allowing greater flexibility when working with scanned environments.

Stunad Spatial is an ongoing experimental research project exploring performance limits, spatial indexing strategies, and interaction models for real-time point cloud environments. The work serves as a foundation for future tools aimed at XR design workflows and spatial computing systems.

Point clouds are rapidly becoming a fundamental component of spatial computing, digital twins, and XR pipelines. By treating spatial data as a computational medium rather than simply visual output, this project explores new possibilities for how designers and engineers interact with the physical world through digital tools.