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» Matching 2.5D Scans for Face Recognition
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ICBA
2004
Springer
224views Biometrics» more  ICBA 2004»
13 years 10 months ago
Matching 2.5D Scans for Face Recognition
Abstract. The performance of face recognition systems that use twodimensional images is dependent on consistent conditions such as lighting, pose, and facial appearance. We are dev...
Xiaoguang Lu, Dirk Colbry, Anil K. Jain
PAMI
2006
227views more  PAMI 2006»
13 years 4 months ago
Matching 2.5D Face Scans to 3D Models
The performance of face recognition systems that use two-dimensional images depends on factors such as lighting and subject's pose. We are developing a face recognition system...
Xiaoguang Lu, Anil K. Jain, Dirk Colbry
AVSS
2009
IEEE
13 years 2 months ago
3D Face Recognition Using Multiview Keypoint Matching
A novel algorithm for 3D face recognition based point cloud rotations, multiple projections, and voted keypoint matching is proposed and evaluated. The basic idea is to rotate eac...
Michael Mayo, Edmond Zhang
ECCV
2008
Springer
14 years 6 months ago
3D Face Model Fitting for Recognition
This paper presents an automatic efficient method to fit a statistical deformation model of the human face to 3D scan data. In a global to local fitting scheme, the shape parameter...
Frank B. ter Haar, Remco C. Veltkamp
ICPR
2004
IEEE
14 years 6 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 developi...
Anil K. Jain, Dirk Colbry, Xiaoguang Lu