Perception

Disparity Map

Disparity Map is an image encoding, for each pixel, the horizontal offset between its projections in a rectified stereo pair. Disparity is inversely proportional to depth given the cameras' focal length and baseline, so an accurate disparity map is equivalent to a metric depth map. Classical block matching and semi-global matching have been largely superseded by learned stereo networks, though textureless and reflective regions remain difficult.

Why it matters for physical AI

Stereo disparity provides metrically scaled depth from passive cameras, a robust and inexpensive geometry source for outdoor navigation and manipulation where active depth sensors wash out or interfere.