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IPSN
2004
Springer
15 years 3 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
48
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ACCV
2009
Springer
15 years 4 months ago
Twisted Cubic: Degeneracy Degree and Relationship with General Degeneracy
Fundamental matrix, drawing geometric relationship between two images, plays an important role in 3-dimensional computer vision. Degenerate configurations of space points and two ...
Tian Lan, Yihong Wu, Zhanyi Hu
ECCV
2010
Springer
14 years 8 months ago
Sequential Non-Rigid Structure-from-Motion with the 3D-Implicit Low-Rank Shape Model
So far the Non-Rigid Structure-from-Motion problem has been tackled using a batch approach. All the frames are processed at once after the video acquisition takes place. In this pa...
Marco Paladini, Adrien Bartoli, Lourdes de Agapito
IVCNZ
1998
14 years 11 months ago
On Estimation of Fundamental Matrix in Computational Stereo
We address the problem of estimating a fundamental matrix from a given set of corresponding pixels in two perspective images of a 3D scene that form a stereopair. The 3x3 fundamen...
Yuping Li, Georgy L. Gimel'farb
NIPS
2008
14 years 11 months ago
Covariance Estimation for High Dimensional Data Vectors Using the Sparse Matrix Transform
Covariance estimation for high dimensional vectors is a classically difficult problem in statistical analysis and machine learning. In this paper, we propose a maximum likelihood ...
Guangzhi Cao, Charles A. Bouman