Three-dimensional face recognition

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Three-dimensional face recognition (3D face recognition) is a modality of facial recognition methods in which the three-dimensional geometry of the human face is used. It has been shown that 3D face recognition methods can achieve significantly higher accuracy than their 2D counterparts, rivaling fingerprint recognition.

3D face recognition achieves better accuracy than its 2D counterpart by measuring geometry of rigid features on the face.^{[citation needed]} 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.

The main technological limitation of 3D face recognition methods is the acquisition of 3D images, which usually requires a range camera. This is also a reason why 3D face recognition methods have emerged significantly later (in the late 1980s) than 2D methods. Recently 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. This allows for good recognition accuracy with low cost off-the-shelf components.

Currently, 3D face recognition is still an open research field, though several vendors already offer commercial solutions.

[edit] See also

Face recognition

[edit] References

Bronstein, A. M.; Bronstein, M.M, and Kimmel, R. (2005). "Three-dimensional face recognition". International Journal of Computer Vision (IJCV) 64 (1): 5-30.