30 search results - page 2 / 6 » Weighted and robust learning of subspace representations |
ICCV
2007
IEEE
14 years 7 months ago
2007
IEEE
Most existing subspace analysis-based tracking algorithms utilize a flattened vector to represent a target, resulting in a high dimensional data learning problem. Recently, subspa...
CVPR
2012
IEEE
11 years 7 months ago
2012
IEEE
Subspace clustering and feature extraction are two of the most commonly used unsupervised learning techniques in computer vision and pattern recognition. State-of-theart technique...
JMLR
2012
11 years 7 months ago
2012
A challenging problem of multi-label learning is that both the label space and the model complexity will grow rapidly with the increase in the number of labels, and thus makes the...
ICPR
2004
IEEE
14 years 6 months ago
2004
IEEE
In the past decade or so, subspace methods have been largely used in face recognition ? generally with quite success. Subspace approaches, however, generally assume the training d...
BVAI
2007
Springer
13 years 11 months ago
2007
Springer
In real life, visual learning is supposed to be a continuous process. Humans have an innate facility to recognize objects even under less-than-ideal conditions and to build robust ...