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» Maximum kernel density estimator for robust fitting
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NIPS
2004
13 years 8 months ago
Sampling Methods for Unsupervised Learning
We present an algorithm to overcome the local maxima problem in estimating the parameters of mixture models. It combines existing approaches from both EM and a robust fitting algo...
Robert Fergus, Andrew Zisserman, Pietro Perona
CVPR
2005
IEEE
14 years 9 months ago
The Modified pbM-Estimator Method and a Runtime Analysis Technique for the RANSAC Family
Robust regression techniques are used today in many computer vision algorithms. Chen and Meer recently presented a new robust regression technique named the projection based M-est...
Stas Rozenfeld, Ilan Shimshoni
CVPR
2006
IEEE
14 years 9 months ago
Efficient Nonparametric Belief Propagation with Application to Articulated Body Tracking
An efficient Nonparametric Belief Propagation (NBP) algorithm is developed in this paper. While the recently proposed nonparametric belief propagation algorithm has wide applicati...
Tony X. Han, Huazhong Ning, Thomas S. Huang
PAKDD
2005
ACM
142views Data Mining» more  PAKDD 2005»
14 years 29 days ago
Dynamic Cluster Formation Using Level Set Methods
Density-based clustering has the advantages for (i) allowing arbitrary shape of cluster and (ii) not requiring the number of clusters as input. However, when clusters touch each o...
Andy M. Yip, Chris H. Q. Ding, Tony F. Chan
ECCV
2002
Springer
14 years 9 months ago
Nonlinear Shape Statistics in Mumford-Shah Based Segmentation
We present a variational integration of nonlinear shape statistics into a Mumford?Shah based segmentation process. The nonlinear statistics are derived from a set of training silho...
Christoph Schnörr, Daniel Cremers, Timo Kohlb...