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» Object recognition using graph spectral invariants
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CVPR
2008
IEEE
14 years 11 months ago
Unsupervised learning of probabilistic object models (POMs) for object classification, segmentation and recognition
We present a new unsupervised method to learn unified probabilistic object models (POMs) which can be applied to classification, segmentation, and recognition. We formulate this a...
Yuanhao Chen, Long Zhu, Alan L. Yuille, HongJiang ...
IJCV
1998
121views more  IJCV 1998»
13 years 8 months ago
Generalization to Novel Views: Universal, Class-based, and Model-based Processing
A major problem in object recognition is that a novel image of a given object can be different from all previously seen images. Images can vary considerably due to changes in viewi...
Yael Moses, Shimon Ullman
ICCV
2007
IEEE
14 years 11 months ago
Illumination and Affine- Invariant Point Matching using an Ordinal Approach
We present an approach for illumination and affineinvariant point matching using ordinal features. Ordinal measures for matching only consider the order between pixels and not the...
Raj Gupta, Anurag Mittal
ICASSP
2009
IEEE
14 years 3 months ago
Bispectrum on finite groups
The algebraic theory of finite groups appears in signal processing problems involving the statistical analysis of ranked data and the construction of invariants for pattern recog...
Ramakrishna Kakarala
ICCV
2003
IEEE
14 years 11 months ago
Graph Partition by Swendsen-Wang Cuts
Vision tasks, such as segmentation, grouping, recognition, can be formulated as graph partition problems. The recent literature witnessed two popular graph cut algorithms: the Ncu...
Adrian Barbu, Song Chun Zhu