3D Reconstruction
xtan explores 3D reconstruction workflows where stereo vision, spatial tracking, and geometry-aware sensing support the reconstruction of real-world environments and objects in digital 3D space.
Reconstructing real-world geometry
3D reconstruction techniques convert visual data into digital spatial representations. Stereo vision pipelines may support experimental workflows where multiple camera views help reconstruct geometry, surfaces, and spatial structures from real environments.
Potential for research and spatial analysis
3D reconstruction is widely used in robotics, mapping, digital twins, and scientific research. Geometry-aware sensing may support environments where spatial data is analyzed to better understand objects, environments, and motion in real-world scenes.
Why xtan can be relevant
xtan focuses on stereo vision, geometry-first interaction, and practical spatial systems. Within 3D reconstruction workflows this may support spatial capture experiments, environment reconstruction pipelines, and research into geometry-based perception systems.