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IVC
2000
188views more  IVC 2000»
13 years 4 months ago
Face recognition by statistical analysis of feature detectors
A successful face recognition system calculates similarity of face images based on the activation of multiscale and multiorientation Gabor kernels, but without utilizing any stati...
Peter Kalocsai, Christoph von der Malsburg, J. Hor...
CVPR
2004
IEEE
14 years 6 months ago
How Features of the Human Face Affect Recognition: A Statistical Comparison of Three Face Recognition Algorithms
Recognition difficulty is statistically linked to ??? subject covariate factors such as age and gender for three face recognition algorithms: principle components analysis, an int...
Geof H. Givens, J. Ross Beveridge, Bruce A. Draper...
PR
2007
192views more  PR 2007»
13 years 4 months ago
Face detection with boosted Gaussian features
Detecting faces in images is a key step in numerous computer vision applications, such as face recognition or facial expression analysis. Automatic face detection is a difficult ...
Julien Meynet, Vlad Popovici, Jean-Philippe Thiran
ICIAR
2010
Springer
13 years 9 months ago
Adaptation of SIFT Features for Robust Face Recognition
Abstract. The Scale Invariant Feature Transform (SIFT) is an algorithm used to detect and describe scale-, translation- and rotation-invariant local features in images. The origina...
Janez Krizaj, Vitomir Struc, Nikola Pavesic
SCIA
2009
Springer
195views Image Analysis» more  SCIA 2009»
13 years 9 months ago
Multi-band Gradient Component Pattern (MGCP): A New Statistical Feature for Face Recognition
A feature extraction method using multi-frequency bands is proposed for face recognition, named as the Multi-band Gradient Component Pattern (MGCP). The MGCP captures discriminativ...
Yimo Guo, Jie Chen, Guoying Zhao, Matti Pietik&aum...