= Stereo vision
<Stereo vision> estimates three-dimensional structure from images taken at different viewpoints. After <camera calibration> and alignment into a common image geometry, a point's horizontal displacement between the two views is its <stereo disparity> $d$. For parallel ideal cameras with <camera baseline> $B$ and <focal length> $f$ in pixel units, similar triangles give
$$
Z=\frac{fB}{d}.
$$
For $f=800$ pixels, $B=0.10\,\mathrm m$ and $d=40$ pixels, the inferred depth is $2\,\mathrm m$. Doubling the depth halves the <stereo disparity>, making distant structure harder to measure accurately.<What Is Stereo Reconstruction? by MathWorks>[How Does Stereo Reconstruction Work?, disparity-to-depth equation]{ref}
A practical apparatus uses two rigidly mounted <cameras>, a calibration target and synchronized exposures. Matching the same physical feature is essential: repeated textures, hidden surfaces and motion can give false correspondences. The measurement is therefore geometric inference from matched observations, not an intrinsic depth label stored in each <pixel>.<What Is Stereo Reconstruction? by MathWorks>[correspondence and triangulation explanation]{ref}
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