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» Solving Sparse Linear Constraints
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IPSN
2004
Springer
15 years 4 months ago
Estimation from lossy sensor data: jump linear modeling and Kalman filtering
Due to constraints in cost, power, and communication, losses often arise in large sensor networks. The sensor can be modeled as an output of a linear stochastic system with random...
Alyson K. Fletcher, Sundeep Rangan, Vivek K. Goyal
ICCV
2009
IEEE
1957views Computer Vision» more  ICCV 2009»
16 years 4 months ago
Robust Visual Tracking using L1 Minimization
In this paper we propose a robust visual tracking method by casting tracking as a sparse approximation problem in a particle filter framework. In this framework, occlusion, corru...
Xue Mei, Haibin Ling
CIMAGING
2010
195views Hardware» more  CIMAGING 2010»
15 years 13 days ago
SPIRAL out of convexity: sparsity-regularized algorithms for photon-limited imaging
The observations in many applications consist of counts of discrete events, such as photons hitting a detector, which cannot be effectively modeled using an additive bounded or Ga...
Zachary T. Harmany, Roummel F. Marcia, Rebecca Wil...
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PAMI
2008
147views more  PAMI 2008»
14 years 11 months ago
Image Stitching Using Structure Deformation
The aim of this paper is to achieve seamless image stitching without producing visual artifact caused by severe intensity discrepancy and structure misalignment, given that the inp...
Jiaya Jia, Chi-Keung Tang
PAMI
2007
138views more  PAMI 2007»
14 years 10 months ago
A Fast Biologically Inspired Algorithm for Recurrent Motion Estimation
—We have previously developed a neurodynamical model of motion segregation in cortical visual area V1 and MT of the dorsal stream. The model explains how motion ambiguities cause...
Pierre Bayerl, Heiko Neumann