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» Learning Statistical Structure for Object Detection
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CVPR
2009
IEEE
15 years 2 months ago
Constrained Marginal Space Learning for Efficient 3D Anatomical Structure Detection in Medical Images
Recently, we proposed marginal space learning (MSL) as a generic approach for automatic detection of 3D anatom- ical structures in many medical imaging modalities. To accurately...
Yefeng Zheng, Bogdan Georgescu, Haibin Ling, Shaoh...
IVC
2008
101views more  IVC 2008»
13 years 7 months ago
Occlusion analysis: Learning and utilising depth maps in object tracking
Complex scenes such as underground stations and malls are composed of static occlusion structures such as walls, entrances, columns, turnstiles and barriers. Unless this occlusion...
Darrel Greenhill, John-Paul Renno, James Orwell, G...
CVPR
2005
IEEE
14 years 9 months ago
Spatial Priors for Part-Based Recognition Using Statistical Models
We present a class of statistical models for part-based object recognition that are explicitly parameterized according to the degree of spatial structure they can represent. These...
David J. Crandall, Pedro F. Felzenszwalb, Daniel P...
3DOR
2010
13 years 2 months ago
Learning the Compositional Structure of Man-Made Objects for 3D Shape Retrieval
While approaches based on local features play a more and more important role for 3D shape retrieval, the problems of feature selection and similarity measurement between sets of l...
Raoul Wessel, Reinhard Klein
CVPR
2012
IEEE
11 years 10 months ago
Learning to localize detected objects
In this paper, we propose an approach to accurately localize detected objects. The goal is to predict which features pertain to the object and define the object extent with segme...
Qieyun Dai, Derek Hoiem