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AAAI
2008
13 years 8 months ago
Manifold Integration with Markov Random Walks
Most manifold learning methods consider only one similarity matrix to induce a low-dimensional manifold embedded in data space. In practice, however, we often use multiple sensors...
Heeyoul Choi, Seungjin Choi, Yoonsuck Choe
PAMI
2006
178views more  PAMI 2006»
13 years 6 months ago
Learning Nonlinear Image Manifolds by Global Alignment of Local Linear Models
Appearance-based methods, based on statistical models of the pixel values in an image (region) rather than geometrical object models, are increasingly popular in computer vision. I...
Jakob J. Verbeek
CVPR
2007
IEEE
14 years 8 months ago
Differential Camera Tracking through Linearizing the Local Appearance Manifold
The appearance of a scene is a function of the scene contents, the lighting, and the camera pose. A set of n-pixel images of a non-degenerate scene captured from different perspec...
Hua Yang, Marc Pollefeys, Greg Welch, Jan-Michael ...
ICML
2008
IEEE
14 years 7 months ago
ManifoldBoost: stagewise function approximation for fully-, semi- and un-supervised learning
We introduce a boosting framework to solve a classification problem with added manifold and ambient regularization costs. It allows for a natural extension of boosting into both s...
Nicolas Loeff, David A. Forsyth, Deepak Ramachandr...
DGCI
2006
Springer
13 years 10 months ago
Improving Difference Operators by Local Feature Detection
Differential operators are required to compute several characteristics for continuous surfaces, as e.g. tangents, curvature, flatness, shape descriptors. We propose to replace diff...
Kristof Teelen, Peter Veelaert