3D face recognition with the average-half-face

We present a promising analysis on using the pattern of symmetry in the face to increase the accuracy of three-dimensional face recognition. We introduce the concept of the dasiaaverage-half-facepsila, motivated by the symmetry preserving singular value decomposition. We compare face recognition results using the eigenfaces face recognition algorithm with average-half-face data and full face data in several experiments on a 3D face data set of 1126 images. We show that the results from the eigenfaces face recognition system using the average-half-face is more accurate than using the full face, only the left or right half of the face or a random choice of half of the face.