 Stereoscopy

Stereoscopy uses images from different viewpoints to convey or recover depth. In scientific photography, identifying the same feature in two calibrated views permits stereoscopic triangulation: intersecting the directions inferred from the two images.^[ref]

Consider ideal cameras with parallel axes, separated by a baseline $B$. With matching forward-projection coordinates and common focal length $f$ in image-coordinate units, a point at $(X,Z)$ projects toSubtracting gives the stereo disparity $d=x_L-x_R=fB/Z$, hence $Z=fB/d$. If $f$ and $d$ are measured in pixels, $Z$ has the same length unit as $B$.

For an original example, $B=0.12\mathrm{m}$, $f=800$ pixels and $d=24$ pixels give $Z=4\mathrm{m}$. First-order propagation of uncertainty gives ${\sigma }_Z\simeq fB{\sigma }_d/d^2$. Thus fixed disparity precision produces increasing depth uncertainty for more distant objects. Correctly matching the same feature is also essential; ambiguous or hidden features can defeat the reconstruction even when the geometry is known.