Abstract
In this paper, we present a local appearance-based approach for 3-D face recognition. In the proposed algorithm, we first register the 3-D point clouds to provide a dense correspondence between faces. Afterwards, we analyze two mapping techniques-the closest-point mapping and the ray-casting mapping, to construct depth images from the corresponding well-registered point clouds. The depth images that are obtained are then divided into local regions where the discrete cosine transformation is performed to extract local information. The local features are combined at the feature level for classification. Experimental results on the FRGC version 2.0 face database show that the proposed algorithm performs superior to the well-known face recognition algorithms.
Original language | English (US) |
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Pages (from-to) | 630-636 |
Number of pages | 7 |
Journal | IEEE Transactions on Information Forensics and Security |
Volume | 2 |
Issue number | 3 |
DOIs | |
State | Published - Sep 2007 |
Keywords
- 3-D face recognition
- Automatic registration
- Depth image
- Local appearance face recognition
ASJC Scopus subject areas
- Safety, Risk, Reliability and Quality
- Computer Networks and Communications