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Proceedings Paper

3D FaceCam: a fast and accurate 3D facial imaging device for biometrics applications
Author(s): Jason Geng; Ping Zhuang; Patrick May; Steven Yi; David Tunnell
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Paper Abstract

Human faces are fundamentally three-dimensional (3D) objects, and each face has its unique 3D geometric profile. The 3D geometric features of a human face can be used, together with its 2D texture, for rapid and accurate face recognition purposes. Due to the lack of low-cost and robust 3D sensors and effective 3D facial recognition (FR) algorithms, almost all existing FR systems use 2D face images. Genex has developed 3D solutions that overcome the inherent problems in 2D while also addressing limitations in other 3D alternatives. One important aspect of our solution is a unique 3D camera (the 3D FaceCam) that combines multiple imaging sensors within a single compact device to provide instantaneous, ear-to-ear coverage of a human face. This 3D camera uses three high-resolution CCD sensors and a color encoded pattern projection system. The RGB color information from each pixel is used to compute the range data and generate an accurate 3D surface map. The imaging system uses no moving parts and combines multiple 3D views to provide detailed and complete 3D coverage of the entire face. Images are captured within a fraction of a second and full-frame 3D data is produced within a few seconds. This described method provides much better data coverage and accuracy in feature areas with sharp features or details (such as the nose and eyes). Using this 3D data, we have been able to demonstrate that a 3D approach can significantly improve the performance of facial recognition. We have conducted tests in which we have varied the lighting conditions and angle of image acquisition in the "field." These tests have shown that the matching results are significantly improved when enrolling a 3D image rather than a single 2D image. With its 3D solutions, Genex is working toward unlocking the promise of powerful 3D FR and transferring FR from a lab technology into a real-world biometric solution.

Paper Details

Date Published: 25 August 2004
PDF: 12 pages
Proc. SPIE 5404, Biometric Technology for Human Identification, (25 August 2004); doi: 10.1117/12.542208
Show Author Affiliations
Jason Geng, Genex Technologies, Inc. (United States)
Ping Zhuang, Genex Technologies, Inc. (United States)
Patrick May, Genex Technologies, Inc. (United States)
Steven Yi, Genex Technologies, Inc. (United States)
David Tunnell, Genex Technologies, Inc. (United States)

Published in SPIE Proceedings Vol. 5404:
Biometric Technology for Human Identification
Anil K. Jain; Nalini K. Ratha, Editor(s)

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