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» Learning bilinear models for two-factor problems in vision
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ECCV
2002
Springer
14 years 11 months ago
Probabilistic Search for Object Segmentation and Recognition
Abstract. The problem of searching for a model-based scene interpretation is analyzed within a probabilistic framework. Object models are formulated as generative models for range ...
Ulrich Hillenbrand, Gerd Hirzinger
EMMCVPR
2007
Springer
14 years 3 months ago
Compositional Object Recognition, Segmentation, and Tracking in Video
Abstract. The complexity of visual representations is substantially limited by the compositional nature of our visual world which, therefore, renders learning structured object mod...
Björn Ommer, Joachim M. Buhmann
CVPR
2009
IEEE
15 years 4 months ago
Co-training with Noisy Perceptual Observations
Many perception and multimedia indexing problems involve datasets that are naturally comprised of multiple streams or modalities for which supervised training data is only sparsely...
Ashish Kapoor, Chris Mario Christoudias, Raquel Ur...
ICCV
2009
IEEE
15 years 2 months ago
Scene Shape Priors for Superpixel Segmentation
Unsupervised over-segmentation of an image into superpixels is a common preprocessing step for image parsing algorithms. Superpixels are used as both regions of support for feat...
Alastair P. Moore, Simon J. D. Prince, Jonathan Wa...
CVPR
2012
IEEE
11 years 11 months ago
Discrete texture traces: Topological representation of geometric context
Modeling representations of image patches that are quasi-invariant to spatial deformations is an important problem in computer vision. In this paper, we propose a novel concept, t...
Jan Ernst, Maneesh Kumar Singh, Visvanathan Ramesh