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» An Efficient Method for Compressed Sensing
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JSCIC
2010
231views more  JSCIC 2010»
13 years 2 months ago
Geometric Applications of the Split Bregman Method: Segmentation and Surface Reconstruction
Variational models for image segmentation have many applications, but can be slow to compute. Recently, globally convex segmentation models have been introduced which are very rel...
Tom Goldstein, Xavier Bresson, Stanley Osher
TSP
2010
13 years 2 months ago
Methods for sparse signal recovery using Kalman filtering with embedded pseudo-measurement norms and quasi-norms
We present two simple methods for recovering sparse signals from a series of noisy observations. The theory of compressed sensing (CS) requires solving a convex constrained minimiz...
Avishy Carmi, Pini Gurfil, Dimitri Kanevsky
ECCV
2008
Springer
14 years 9 months ago
Efficient Edge-Based Methods for Estimating Manhattan Frames in Urban Imagery
We address the problem of efficiently estimating the rotation of a camera relative to the canonical 3D Cartesian frame of an urban scene, under the so-called "Manhattan World&...
Patrick Denis, James H. Elder, Francisco J. Estrad...
VLDB
2007
ACM
130views Database» more  VLDB 2007»
14 years 7 months ago
A Simple and Efficient Estimation Method for Stream Expression Cardinalities
Estimating the cardinality (i.e. number of distinct elements) of an arbitrary set expression defined over multiple distributed streams is one of the most fundamental queries of in...
Aiyou Chen, Jin Cao, Tian Bu
TSP
2010
13 years 2 months ago
Decentralized sparse signal recovery for compressive sleeping wireless sensor networks
Abstract--This paper develops an optimal decentralized algorithm for sparse signal recovery and demonstrates its application in monitoring localized phenomena using energy-constrai...
Qing Ling, Zhi Tian