A VR volume visualization framework that clusters Gaussian splats into selectable super-Gaussians and couples brush-based selection with natural language queries for interactive scene editing.
syGlass: Interactive Exploration of Multidimensional Images Using Virtual Reality Head-mounted Displays
1 Pith paper cite this work, alongside 34 external citations. Polarity classification is still indexing.
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abstract
The quest for deeper understanding of biological systems has driven the acquisition of increasingly larger multidimensional image datasets. Inspecting and manipulating data of this complexity is very challenging in traditional visualization systems. We developed syGlass, a software package capable of visualizing large scale volumetric data with inexpensive virtual reality head-mounted display technology. This allows leveraging stereoscopic vision to significantly improve perception of complex 3D structures, and provides immersive interaction with data directly in 3D. We accomplished this by developing highly optimized data flow and volume rendering pipelines, tested on datasets up to 16TB in size, as well as tools available in a virtual reality GUI to support advanced data exploration, annotation, and cataloguing.
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Super-Gaussian: Interactive Scene Editing for 3D Gaussian Splatting and NLI-Based Volume Visualization in Virtual Reality
A VR volume visualization framework that clusters Gaussian splats into selectable super-Gaussians and couples brush-based selection with natural language queries for interactive scene editing.