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» Object Detection Using a Cascade of 3D Models
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IPMI
2003
Springer
16 years 3 months ago
Evaluation of 3D Correspondence Methods for Model Building
Abstract. The correspondence problem is of high relevance in the construction and use of statistical models. Statistical models are used for a variety of medical application, e.g. ...
Martin Styner, Kumar T. Rajamani, Lutz-Peter Nolte...
NIPS
2004
15 years 4 months ago
Contextual Models for Object Detection Using Boosted Random Fields
We seek to both detect and segment objects in images. To exploit both local image data as well as contextual information, we introduce Boosted Random Fields (BRFs), which use boos...
Antonio Torralba, Kevin P. Murphy, William T. Free...
CVPR
2005
IEEE
16 years 4 months ago
Discriminative Learning of Markov Random Fields for Segmentation of 3D Scan Data
We address the problem of segmenting 3D scan data into objects or object classes. Our segmentation framework is based on a subclass of Markov Random Fields (MRFs) which support ef...
Dragomir Anguelov, Benjamin Taskar, Vassil Chatalb...
CVPR
2006
IEEE
16 years 4 months ago
A Dynamic Bayesian Network Model for Autonomous 3D Reconstruction from a Single Indoor Image
When we look at a picture, our prior knowledge about the world allows us to resolve some of the ambiguities that are inherent to monocular vision, and thereby infer 3d information...
Erick Delage, Honglak Lee, Andrew Y. Ng
ICCV
2009
IEEE
15 years 17 days ago
Modeling 3D human poses from uncalibrated monocular images
This paper introduces an efficient algorithm that reconstructs 3D human poses as well as camera parameters from a small number of 2D point correspondences obtained from uncalibrat...
Xiaolin K. Wei, Jinxiang Chai