Real-time identification using a canonical face depth map

A practical identification system based on 3D face scanning is presented. The speed of comparing a probe scan to the gallery is enabled by scan normalisation followed by extraction of higher level features. Our canonical face depth map (CFDM) is a standardised representation for three-dimensional (3D) face data in a face-based coordinate system. Our experiments demonstrate that the CFDM normalisation algorithm is (a) robust to noise and occlusion, (b) significantly reduces storage requirements and thus I/O time, and (c) improves the efficiency of face recognition algorithms. Producing the CFDM takes less than a second on a desktop for 320 times 240 rangel scans. Current 3D scanning and matching methods are too slow for person identification, even for a watch list of only a few hundred face models. Transforming scanned 3D faces into CFDM format enables a probe scan to be matched to hundreds or thousands of gallery scans in a fewtimesseconds on a commodity computer. The best results achieved so far are a rank-1 recognition rate of 98.2% and a speed of 1900 face matches per second. Extrapolating these results suggests that multistage systems could achieve even better performance on even larger galleries.