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» Using Component Features for Face Recognition
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ICMCS
2006
IEEE
215views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Biologically vs. Logic Inspired Encoding of Facial Actions and Emotions in Video
Automatic facial expression analysis is an important aspect of Human Machine Interaction as the face is an important communicative medium. We use our face to signal interest, disa...
Michel François Valstar, Maja Pantic
ICASSP
2009
IEEE
14 years 2 months ago
On separating glottal source and vocal tract information in telephony speaker verification
The popular mel-frequency cepstral coefficients (MFCCs) capture a mixture of speaker-related, phonemic and channel information. Speaker-related information could be further broke...
Tomi Kinnunen, Paavo Alku
BMCBI
2010
155views more  BMCBI 2010»
13 years 7 months ago
A flexible R package for nonnegative matrix factorization
Background: Nonnegative Matrix Factorization (NMF) is an unsupervised learning technique that has been applied successfully in several fields, including signal processing, face re...
Renaud Gaujoux, Cathal Seoighe
MM
2004
ACM
248views Multimedia» more  MM 2004»
14 years 1 months ago
Incremental semi-supervised subspace learning for image retrieval
Subspace learning techniques are widespread in pattern recognition research. They include Principal Component Analysis (PCA), Locality Preserving Projection (LPP), etc. These tech...
Xiaofei He
CVPR
2000
IEEE
14 years 9 months ago
Towards Automatic Discovery of Object Categories
We propose a method to learn heterogeneous models of object classes for visual recognition. The training images contain a preponderance of clutter and learning is unsupervised. Ou...
Markus Weber, Max Welling, Pietro Perona