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» Large Scale Learning of Active Shape Models
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3DIM
1999
IEEE
15 years 2 months ago
Large Data Sets and Confusing Scenes in 3-D Surface Matching and Recognition
In this paper, we report on recent extensions to a surface matching algorithm based on local 3-D signatures. This algorithm was previously shown to be effective in view registrati...
Owen T. Carmichael, Daniel F. Huber, Martial Heber...
CVPR
2012
IEEE
13 years 3 days ago
Linear solution to scale invariant global figure ground separation
We propose a novel linear method for scale invariant figure ground separation in images and videos. Figure ground separation is treated as a superpixel labeling problem. We optim...
Hao Jiang
TMI
2002
259views more  TMI 2002»
14 years 9 months ago
3-D Active Appearance Models: Segmentation of Cardiac MR and Ultrasound Images
A model-based method for three-dimensional image segmentation was developed and its performance assessed in segmentation of volumetric cardiac magnetic resonance (MR) images and ec...
Steven C. Mitchell, Johan G. Bosch, Boudewijn P. F...
89
Voted
PERCOM
2007
ACM
15 years 9 months ago
Structural Learning of Activities from Sparse Datasets
Abstract. A major challenge in pervasive computing is to learn activity patterns, such as bathing and cleaning from sensor data. Typical sensor deployments generate sparse datasets...
Fahd Albinali, Nigel Davies, Adrian Friday
84
Voted
ICDM
2009
IEEE
207views Data Mining» more  ICDM 2009»
14 years 7 months ago
Spatially Adaptive Classification and Active Learning of Multispectral Data with Gaussian Processes
Multispectral remote sensing images are widely used for automated land use and land cover classification tasks. Remotely sensed images usually cover large geographical areas, and s...
Goo Jun, Ranga Raju Vatsavai, Joydeep Ghosh