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» A probabilistic framework for image segmentation
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ICCV
2005
IEEE
14 years 1 months ago
Learning Hierarchical Models of Scenes, Objects, and Parts
We describe a hierarchical probabilistic model for the detection and recognition of objects in cluttered, natural scenes. The model is based on a set of parts which describe the e...
Erik B. Sudderth, Antonio B. Torralba, William T. ...
CVPR
2011
IEEE
13 years 5 months ago
Sparsity-based Image Denoising via Dictionary Learning and Structural Clustering
Where does the sparsity in image signals come from? Local and nonlocal image models have supplied complementary views toward the regularity in natural images the former attempts t...
Weisheng Dong, Xin Li
ICIP
2007
IEEE
14 years 9 months ago
A Statistical Approach for Intensity Loss Compensation of Confocal Microscopy Images
In this paper a probabilistic technique for compensation of intensity loss in the confocal microscopy images is presented. Confocal microscopy images are modeled as a mixture of t...
Sowmya Gopinath, Ninad Thakoor, Jean Gao, Kate Lub...
EMMCVPR
2007
Springer
14 years 2 months ago
Bottom-Up Recognition and Parsing of the Human Body
Recognizing humans, estimating their pose and segmenting their body parts are key to high-level image understanding. Because humans are highly articulated, the range of deformation...
Praveen Srinivasan, Jianbo Shi
DAGM
2006
Springer
13 years 11 months ago
On-Line, Incremental Learning of a Robust Active Shape Model
Abstract. Active Shape Models are commonly used to recognize and locate different aspects of known rigid objects. However, they require an off-line learning stage, such that the ex...
Michael Fussenegger, Peter M. Roth, Horst Bischof,...