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ICMCS
2005
IEEE
113views Multimedia» more  ICMCS 2005»
14 years 2 months ago
HMM-Based Deception Recognition from Visual Cues
Behavioral indicators of deception and behavioral state are extremely difficult for humans to analyze. This research effort attempts to leverage automated systems to augment human...
Gabriel Tsechpenakis, Dimitris N. Metaxas, Mark Ad...
CVPR
2011
IEEE
13 years 5 months ago
On Deep Generative Models with Applications to Recognition
The most popular way to use probabilistic models in vision is first to extract some descriptors of small image patches or object parts using well-engineered features, and then to...
Marc', Aurelio Ranzato, Joshua Susskind, Volodymyr...
ACCV
2010
Springer
13 years 4 months ago
3D Object Recognition Based on Canonical Angles between Shape Subspaces
We propose a method to measure similarity of shape for 3D objects using 3-dimensional shape subspaces produced by the factorization method. We establish an index of shape similarit...
Yosuke Igarashi, Kazuhiro Fukui
TIFS
2008
129views more  TIFS 2008»
13 years 9 months ago
On Empirical Recognition Capacity of Biometric Systems Under Global PCA and ICA Encoding
Performance of biometric-based recognition systems depends on various factors: database quality, image preprocessing, encoding techniques, etc. Given a biometric database and a se...
Natalia A. Schmid, Francesco Nicolo
TKDE
2011
479views more  TKDE 2011»
13 years 4 months ago
Learning Semi-Riemannian Metrics for Semisupervised Feature Extraction
—Discriminant feature extraction plays a central role in pattern recognition and classification. Linear Discriminant Analysis (LDA) is a traditional algorithm for supervised feat...
Wei Zhang, Zhouchen Lin, Xiaoou Tang