3D Face --> The Test Database

Until recently, little three-dimensional face data has been publicly available for research and nothing towards the magnitude required for development and testing of threedimensional face recognition systems. In these investigations we use a new database of 3D face models, recently made available by the University of York, as part of an ongoing project to provide a publicly available 3D Face Database . Face models are generated in sub-second processing time from a single shot with a 3D camera, using a stereo vision technique enhanced by light projection.

For the purpose of these experiments we select a sample of 1770 face models (280 people) captured under the conditions in Figure 2. During data acquisition no effort was made to control lighting conditions. In order to generate face models at various head orientations, subjects were asked to face reference points positioned roughlyabove and below the camera, but no effort was made to enforce precise orientation.


3D models are aligned to face directly forwards before conversion into 60 by 90 pixel depth map representation. We then take a training set of 300 depth maps (50 people), used to compute the scatter matrices described in section 3. The remaining 1470 depth maps (230 people) are then separated into two disjoint sets of equal size (test set A and test set B). We use test set A to analyse the face-key variance throughout surface space, calculate discriminant weightings (see section 4) and compute the
optimum surface space combinations. This leaves set B as an unseen test set to evaluate the final combined system. Both training and test sets contain subjects of various race, age and gender and nobody is present in both the training and test sets.



Figure 2: Example face models taken from the University of York 3D Face Database