Perception
Multi-View Geometry
Multi-view geometry is the mathematical theory relating 3D scene structure to its projections in multiple camera views, systematized in Hartley and Zisserman's standard text. Its core objects include epipolar geometry, the essential and fundamental matrices, homographies, and triangulation, with bundle adjustment jointly refining structure and camera poses. It underlies stereo vision, structure from motion, visual SLAM, and camera calibration.
Why it matters for physical AI
Even as learned perception advances, geometric constraints remain the backbone of camera calibration, visual odometry, and 3D reconstruction, providing the metric scaffolding on which robot spatial reasoning is built.
Build physical AI
Put these concepts to work on real hardware
Axol is a dual-arm robot built for physical AI — teleoperate it, collect demonstrations, and deploy learned policies out of the box.