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BMVC
2010
15 years 7 days ago
Local Gaussian Processes for Pose Recognition from Noisy Inputs
Gaussian processes have been widely used as a method for inferring the pose of articulated bodies directly from image data. While able to model complex non-linear functions, they ...
Martin Fergie, Aphrodite Galata
ICARCV
2006
IEEE
126views Robotics» more  ICARCV 2006»
15 years 8 months ago
Improvement to the Minimization of Hybrid Error Functions for Pose Alignment
— Many problems in computer vision such as pose recovery and structure estimation are formulated as a minimization process. These problems vary in the use of image measurements d...
A. H. Abdul Hafez, C. V. Jawahar
CVPR
2007
IEEE
16 years 4 months ago
Variable Bandwidth Image Denoising Using Image-based Noise Models
This paper introduces a variational formulation for image denoising based on a quadratic function over kernels of variable bandwidth. These kernels are scale adaptive and reflect ...
Noura Azzabou, Nikos Paragios, Frederic Guichard, ...
ICCV
2003
IEEE
16 years 4 months ago
Image Statistics and Anisotropic Diffusion
Many sensing techniques and image processing applications are characterized by noisy, or corrupted, image data. Anisotropic diffusion is a popular, and theoretically well understo...
Hanno Scharr, Michael J. Black, Horst W. Haussecke...
ECCV
2004
Springer
16 years 4 months ago
Multiphase Dynamic Labeling for Variational Recognition-Driven Image Segmentation
Abstract. We propose a variational framework for the integration multiple competing shape priors into level set based segmentation schemes. By optimizing an appropriate cost functi...
Daniel Cremers, Nir A. Sochen, Christoph Schnö...