Photogrammetry
xtan explores photogrammetry workflows where stereo vision, multi-view geometry, and spatial tracking support the reconstruction of real-world environments and objects from visual observations.
Reconstructing environments from images
Photogrammetry techniques reconstruct three-dimensional structures from multiple images taken from different viewpoints. These methods are widely used in mapping, digital heritage, robotics research, and spatial analysis.
Potential for spatial reconstruction and analysis
Modern photogrammetry pipelines combine camera calibration, feature detection, and multi-view geometry to reconstruct objects and environments. Geometry-aware sensing may support workflows where spatial data contributes to reconstruction, mapping, and environment understanding.
Why xtan can be relevant
xtan focuses on stereo vision, geometry-first interaction, and practical spatial systems. Within photogrammetry workflows this may support experimental reconstruction pipelines, spatial perception systems, and research into geometry-based environment capture.