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» Motion vector recovery with Gaussian Process Regression
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CVPR
2012
IEEE
11 years 9 months ago
Detecting regions of interest in dynamic scenes with camera motions
We present a method to detect the regions of interests in moving camera views of dynamic scenes with multiple moving objects. We start by extracting a global motion tendency that ...
Kihwan Kim, Dongryeol Lee, Irfan A. Essa
CORR
2007
Springer
110views Education» more  CORR 2007»
13 years 6 months ago
Information-theoretic limits on sparsity recovery in the high-dimensional and noisy setting
The problem of recovering the sparsity pattern of a fixed but unknown vector β∗ ∈ Rp based on a set of n noisy observations arises in a variety of settings, including subset...
Martin J. Wainwright
ICPR
2010
IEEE
13 years 4 months ago
Regression-Based Multi-view Facial Expression Recognition
We present a regression-based scheme for multi-view facial expression recognition based on 2-D geometric features. We address the problem by mapping facial points (e.g. mouth corn...
Ognjen Rudovic, Ioannis Patras, Maja Pantic
ICIP
2007
IEEE
14 years 8 months ago
3D Human Motion Tracking using Manifold Learning
This paper introduces a framework to track 3D human movement using Gaussian process dynamic model (GPDM) and particle filter. The framework combines the particle filter and discri...
Feng Guo, Gang Qian
ICIP
2006
IEEE
14 years 8 months ago
Estimating Illumination Chromaticity via Kernel Regression
We propose a simple nonparametric linear regression tool, known as kernel regression (KR), to estimate the illumination chromaticity. We design a Gaussian kernel whose bandwidth i...
Vivek Agarwal, Andrei V. Gribok, Andreas Koschan, ...