Abstract
In the domain of 3D face matching, many techniques have been developed as variants of 3D facial matching approaches that reduce the amount of facial data into few 3D curves. In the literature, many curves have been considered: level-curves, radial curves, iso-stripes, crest lines, etc... In this paper, we exploit curve concept to represent 3D facial geometric. First, depth-level curves were extracted to present 3D facial data then, we investigate the dimensionality reduction offered by Random Projection to perform an artificial system for face recognition using Back-propagation neural network. Experiment was conducted using vrml files from FRAV Database considering only one training sample per person.
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