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» Markov Random Field Models in Computer Vision
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MICCAI
2010
Springer
15 years 2 days ago
Nonlinear Embedding towards Articulated Spine Shape Inference Using Higher-Order MRFs
In this paper we introduce a novel approach for inferring articulated spine models from images. A low-dimensional manifold embedding is created from a training set of prior mesh mo...
Samuel Kadoury, Nikos Paragios
CORR
2006
Springer
119views Education» more  CORR 2006»
15 years 1 months ago
Network Inference from Co-Occurrences
The study of networked systems is an emerging field, impacting almost every area of engineering and science, including the important domains of communication systems, biology, soc...
Michael Rabbat, Mário A. T. Figueiredo, Rob...
HUC
2007
Springer
15 years 7 months ago
Tracking Free-Weight Exercises
Weight training, in addition to aerobic exercises, is an important component of a balanced exercise program. However, mechanisms for tracking free weight exercises have not yet bee...
Keng-hao Chang, Mike Y. Chen, John Canny
ICCV
1998
IEEE
16 years 3 months ago
Wormholes in Shape Space: Tracking Through Discontinuous Changes in Shape
Existing object tracking algorithms generally use some form of local optimisation, assuming that an object's position and shape change smoothly over time. In some situations ...
Tony Heap, David Hogg
CVPR
2006
IEEE
15 years 7 months ago
A Generalized EM Approach for 3D Model Based Face Recognition under Occlusions
This paper describes an algorithm for pose and illumination invariant face recognition from a single image under occlusions. The method iteratively estimates the parameters of a 3...
Michael De Smet, Rik Fransens, Luc J. Van Gool