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» Linear Projective Reconstruction from Matching Tensors
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DCC
2010
IEEE
14 years 2 months ago
Block Compressed Sensing of Images Using Directional Transforms
Block-based random image sampling is coupled with a projectiondriven compressed-sensing recovery that encourages sparsity in the domain of directional transforms simultaneously wi...
Sungkwang Mun, James E. Fowler
FGR
2008
IEEE
299views Biometrics» more  FGR 2008»
14 years 2 months ago
Face recognition with occlusions in the training and testing sets
Partial occlusions in face images pose a great problem for most face recognition algorithms. Several solutions to this problem have been proposed over the years – ranging from d...
Hongjun Jia, Aleix M. Martínez
ICIP
2007
IEEE
14 years 9 months ago
Compressed Sensing Image Reconstruction Via Recursive Spatially Adaptive Filtering
We introduce a new approach to image reconstruction from highly incomplete data. The available data are assumed to be a small collection of spectral coef?cients of an arbitrary li...
Karen O. Egiazarian, Alessandro Foi, Vladimir Katk...
ICASSP
2008
IEEE
14 years 2 months ago
Wavelet-domain compressive signal reconstruction using a Hidden Markov Tree model
Compressive sensing aims to recover a sparse or compressible signal from a small set of projections onto random vectors; conventional solutions involve linear programming or greed...
Marco F. Duarte, Michael B. Wakin, Richard G. Bara...
GIS
2009
ACM
14 years 9 months ago
Map Matching and Uncertainty: an Algorithm and Real-World Experiments
A common problem in moving object databases (MOD) is the reconstruction of a trajectory from a trajectory sample (i.e., a finite sequence of time-space points). A typical solution...
Alejandro A. Vaisman, Bart Kuijpers, Bart Moelans,...