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IPSN
2004
Springer
14 years 1 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
ACCV
2009
Springer
14 years 2 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
13 years 6 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
13 years 9 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
13 years 9 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