Three-Dimensional Model Based Face Recognition

14 years 3 months ago
Three-Dimensional Model Based Face Recognition
The performance of face recognition systems that use twodimensional (2D) images is dependent on consistent conditions such as lighting, pose and facial expression. We are developing a multi-view face recognition system that utilizes three-dimensional (3D) information about the face to make the system more robust to these variations. This paper describes a procedure for constructing a database of 3D face models and matching this database to 2.5D face scans which are captured from different views, using coordinate system invariant properties of the facial surface. 2.5D is a simplified 3D (x, y, z) surface representation that contains at most one depth value (z direction) for every point in the (x, y) plane. A robust similarity metric is defined for matching, based on an Iterative Closest Point (ICP) registration process. Results are given for matching a database of 18 3D face models with 113 2.5D face scans.
Anil K. Jain, Dirk Colbry, Xiaoguang Lu
Added 09 Nov 2009
Updated 09 Nov 2009
Type Conference
Year 2004
Where ICPR
Authors Anil K. Jain, Dirk Colbry, Xiaoguang Lu
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