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ICASSP
2008
IEEE
14 years 3 days ago
Maximum kernel density estimator for robust fitting
Robust model fitting plays an important role in many computer vision applications. In this paper, we propose a new robust estimator — Maximum Kernel Density Estimator (MKDE) bas...
Hanzi Wang
CVPR
2006
IEEE
14 years 7 months ago
Acceleration Strategies for Gaussian Mean-Shift Image Segmentation
Gaussian mean-shift (GMS) is a clustering algorithm that has been shown to produce good image segmentations (where each pixel is represented as a feature vector with spatial and r...
Miguel Á. Carreira-Perpiñán
SDM
2004
SIAM
218views Data Mining» more  SDM 2004»
13 years 7 months ago
Mixture Density Mercer Kernels: A Method to Learn Kernels Directly from Data
This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density e...
Ashok N. Srivastava
TIP
2008
169views more  TIP 2008»
13 years 5 months ago
Maximum Likelihood Wavelet Density Estimation With Applications to Image and Shape Matching
Density estimation for observational data plays an integral role in a broad spectrum of applications, e.g. statistical data analysis and information-theoretic image registration. ...
Adrian M. Peter, Anand Rangarajan
CSDA
2006
142views more  CSDA 2006»
13 years 5 months ago
A Bayesian approach to bandwidth selection for multivariate kernel density estimation
: Kernel density estimation for multivariate data is an important technique that has a wide range of applications. However, it has received significantly less attention than its un...
Xibin Zhang, Maxwell L. King, Rob J. Hyndman