Invariant Robust 3-D Face Recognition based on the Hilbert Transform in Spectral Space

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TypeBook Chapter
Subjectcorrelation; face recognition; fourier transform; Hilbert transform; invariant; robust; spectral analysis; reconnaissance faciale; transformée de Fourier; transformée de Hilbert; invariant; robuste; analyse spectrale
AbstractOne of the main objectives of face recognition is to determine whether an acquired face belongs to a reference database and to subsequently identify the corresponding individual. Face recognition has application in, for instance, forensic science and security. A face recognition algorithm, to be useful in real applications, must discriminate in between individuals, process data in realtime and be robust against occlusion, facial expression and noise. A new method for robust recognition of three-dimensional faces is presented. The method is based on harmonic coding, Hilbert transform and spectral analysis of 3-D depth distributions. Experimental results with three-dimensional faces, which were scanned with a laser scanner, are presented. The proposed method recognises a face with various facial expressions in the presence of occlusion, has a good discrimination, is able to compare a face against a large database of faces in real-time and is robust against shot noise and additive noise.
Publication date
AffiliationNRC Institute for Information Technology; National Research Council Canada
Peer reviewedNo
NRC number48724
NPARC number8913231
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Record identifier325c1a48-3371-4dd1-b2d5-a2f60dd2abd5
Record created2009-04-22
Record modified2016-05-09
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