Real-time identification using a canonical face depth map

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Real-time identification using a canonical face depth map

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© The Institution of Engineering and Technology
Published

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 320×240 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 few seconds 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.

Inspec keywords: extrapolation; image matching; face recognition; feature extraction; image representation

Other keywords: real-time identification; scan normalisation; 3D face scanning; feature extraction; canonical face depth map; 3D face data; probe scan; image matching; face recognition; person identification

Subjects: Interpolation and function approximation (numerical analysis); Interpolation and function approximation (numerical analysis); Image recognition; Computer vision and image processing techniques

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