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NIPS
2007
15 years 1 months ago
Sparse Feature Learning for Deep Belief Networks
Unsupervised learning algorithms aim to discover the structure hidden in the data, and to learn representations that are more suitable as input to a supervised machine than the ra...
Marc'Aurelio Ranzato, Y-Lan Boureau, Yann LeCun
ICB
2007
Springer
183views Biometrics» more  ICB 2007»
15 years 1 months ago
Factorial Hidden Markov Models for Gait Recognition
Gait recognition is an effective approach for human identification at a distance. During the last decade, the theory of hidden Markov models (HMMs) has been used successfully in th...
Changhong Chen, Jimin Liang, Haihong Hu, Licheng J...
ICIP
2006
IEEE
16 years 1 months ago
Fusion of Geometrical and Texture Information for Facial Expression Recognition
A novel method based on geometrical and texture information is proposed for facial expression recognition from video sequences. The Discriminant Non-negative Matrix Factorization ...
Irene Kotsia, Nikos Nikolaidis, Ioannis Pitas
ICIP
1997
IEEE
16 years 1 months ago
Using the Fourier Slice Theorem for Representation of Object Views and Models with application to Face Recognition
A novel method unifying viewer and model centered approaches for representing structurally complex 3-D objects like human faces is presented. The uni ed 3D frequency-domain repres...
Dibyendu Nandy, Jezekiel Ben-Arie
ICPR
2004
IEEE
16 years 28 days ago
Texture Analysis using Level-crossing Statistics
We present a novel statistical texture descriptor employing level-crossing statistics. Images are first mapped into 1D signals using space-filling curves, such as Peano or Hilbert...
Carlos Santamaria, Miroslaw Bober, Wieslaw Szajnow...