A depth map assigns a distance-related value to each accepted image location. The geometry must specify whether this means depth along the camera axis or Euclidean distance along the viewing ray. Units, missing values and the coordinate frame are also part of the representation. In calibrated stereoscopy, converting a disparity map through the camera geometry produces depth estimates.[ref]
Depth Map from Stereo Images in the OpenCV-Python tutorials. Basics, disparity inversely proportional to depth
For an ideal camera, suppose a point has coordinates metres. Its axial depth is two metres, but its Euclidean distance from the camera center is metres. The same scene can thus yield different valid numerical maps under different conventions. A missing stereo correspondence requires an invalid-location marker rather than a fabricated depth. Camera calibration and measurement uncertainty determine how confidently accepted values describe the scene.
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