Three-dimensional face recognition

This avoids such pitfalls of 2D face recognition algorithms as change in lighting, different facial expressions, make-up and head orientation.

Another approach is to use the 3D model to improve accuracy of traditional image based recognition by transforming the head into a known view.

This allows combining the output of pure 3D matchers with the more traditional 2D face recognition algorithms, thus yielding better performance (as shown in FRVT 2006).

The main technological limitation of 3D face recognition methods is the acquisition of 3D image, which usually requires a range camera.

commercial solutions have implemented depth perception by projecting a grid onto the face and integrating video capture of it into a high resolution 3D model.