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» Sparse Semi-supervised Learning Using Conjugate Functions
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HUMO
2007
Springer
13 years 12 months ago
Multi-activity Tracking in LLE Body Pose Space
We present a method to simultaneously estimate 3d body pose and action categories from monocular video sequences. Our approach learns a lowdimensional embedding of the pose manifol...
Tobias Jaeggli, Esther Koller-Meier, Luc J. Van Go...
ICASSP
2010
IEEE
13 years 6 months ago
Image-quality prediction of synthetic aperture sonar imagery
This work exploits several machine-learning techniques to address the problem of image-quality prediction of synthetic aperture sonar (SAS) imagery. The objective is to predict th...
David P. Williams
CVIU
2008
126views more  CVIU 2008»
13 years 5 months ago
Optimising dynamic graphical models for video content analysis
A key problem in video content analysis using dynamic graphical models is to learn a suitable model structure given some observed visual data. We propose a Completed Likelihood AI...
Tao Xiang, Shaogang Gong
ICASSP
2011
IEEE
12 years 9 months ago
Using the kernel trick in compressive sensing: Accurate signal recovery from fewer measurements
Compressive sensing accurately reconstructs a signal that is sparse in some basis from measurements, generally consisting of the signal’s inner products with Gaussian random vec...
Hanchao Qi, Shannon Hughes
ISCAS
2006
IEEE
96views Hardware» more  ISCAS 2006»
13 years 11 months ago
On the initialization of the DNMF algorithm
— A subspace supervised learning algorithm named Discriminant Non-negative Matrix Factorization (DNMF) has been recently proposed for classifying human facial expressions. It dec...
Ioan Buciu, Nikos Nikolaidis, Ioannis Pitas