Comparing strategies for 3D face recognition from a 3D sensor

We address the problem of 3D face recognition from 3D data, using different strategies. One strategy (1F-NF), explored earlier, is to match each individual frame to a set of reference frames. A second one (1F-3D) is to replace the set of reference frames by a 3D model resulting from the integration of individual frames. A third strategy (3D-3D) is to use a 3D face model inferred from multiple frames as the input probe. We show that the recognition performance using 3D model to 3D model outperforms the others, at the cost of a delay in response, due to the model building step.