- Camera calibration:
this step involves recovering
the perspective projection matrix
**C**. This matrix captures the intrinsic parameters of the camera, and the rotation and translation between the camera and the global coordinate frame defined by the calibration target. - Projector calibration:
for each sheet of light projected by the projector,
compute the coefficients
*a*,*b*,*c*, and*d*of the equation of the plane (relative to some global reference frame) that contains the sheet of light:*a X*+*b Y*+*c Z*+*d*= 0.

- it deals with scenes that do not contain sufficient features, such as edges or corners, which are associated with intensity discontinuities, for the stereo matching process
- the correspondence problem is totally absent. For each pixel in the image that is illuminated by a particular sheet of light from the projector or laser unit, the plane equation of the sheet of light would have been computed from the projector calibration procedure, simple triangulation is only required to compute the 3-D coordinates of the pixel.
- it gives a very dense depth (or range) map.
- it is applicable to many shape measurement and defect detection projects.

Its shortcomings are:

- the system must be pre-calibrated. Unlike stereo vision systems with two cameras, there exists no self-calibration technique for recovering the geometry between the camera and the projector (or laser) unit.
- for projector and camera pairs: well-controlled lighting is required, such systems are therefore restricted to working only in indoor environments.