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Proceedings Paper

Extracting invariant features of the human face from 3D range data
Author(s): Shoude Chang; Marc Rioux; Chander Prakash Grover
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Paper Abstract

The surface of the human face can be represented by a set of facets. The Phase Fourier Transform (PFT) can be used to transform a facet in the space domain to a peak in the frequency domain. The position and the distribution of the peak represent the orientation and shape of the facet respectively. The PFT of the human face provides a new signature of the face. The intensity of the PFT is invariant to the shift and out-of-plane rotation within a certain angle. It is also scale invariant within a certain range. We have used Circular Harmonic m-r filtering to achieve the in- plane partial rotation invariance. The recognition decision is based on the intensity and performance of the correlation peak.

Paper Details

Date Published: 5 May 2000
PDF: 7 pages
Proc. SPIE 3905, 28th AIPR Workshop: 3D Visualization for Data Exploration and Decision Making, (5 May 2000); doi: 10.1117/12.384873
Show Author Affiliations
Shoude Chang, Institute for National Measurement Standards (Canada)
Marc Rioux, Institute for Information Technology (Canada)
Chander Prakash Grover, Institute for National Measurement Standards (Canada)


Published in SPIE Proceedings Vol. 3905:
28th AIPR Workshop: 3D Visualization for Data Exploration and Decision Making
William R. Oliver, Editor(s)

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