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» Discrete optimization in computer vision
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CVPR
2005
IEEE
16 years 6 months ago
Damped Newton Algorithms for Matrix Factorization with Missing Data
The problem of low-rank matrix factorization in the presence of missing data has seen significant attention in recent computer vision research. The approach that dominates the lit...
A. M. Buchanan, Andrew W. Fitzgibbon
ICCV
2011
IEEE
14 years 4 months ago
Optical Flow Estimation Using Learned Sparse Model
Optical flow estimation is a fundamental and ill-posed problem in computer vision. To recover a dense flow field, appropriate spatial constraints have to be enforced. Recent ad...
Kui Jia, Xiaogang Wang, Xiaoou Tang
ICCV
2007
IEEE
16 years 6 months ago
Stochastic Adaptive Tracking In A Camera Network
We present a novel stochastic, adaptive strategy for tracking multiple people in a large network of video cameras. Similarities between features (appearance and biometrics) observ...
Bi Song, Amit K. Roy Chowdhury
CVPR
2009
IEEE
16 years 11 months ago
Max-Margin Hidden Conditional Random Fields for Human Action Recognition
We present a new method for classification with structured latent variables. Our model is formulated using the max-margin formalism in the discriminative learning literature. We...
Yang Wang 0003, Greg Mori
CVPR
2003
IEEE
16 years 6 months ago
Extracting Dense Features for Visual Correspondence with Graph Cuts
We present a method for extracting dense features from stereo and motion sequences. Our dense feature is defined symmetrically with respect to both images, and it is extracted dur...
Olga Veksler