94 search results - page 1 / 19 » Maximum kernel density estimator for robust fitting |
ICASSP
2008
IEEE
13 years 11 months ago
2008
IEEE
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...
PAMI
2010
13 years 3 months ago
2010
In this paper, we present a new Adaptive Scale Kernel Consensus (ASKC) robust estimator as a generalization of the popular and state-of-the-art robust estimators such as RANSAC (R...
ICVGIP
2004
13 years 6 months ago
2004
Robust model fitting is important for computer vision tasks due to the occurrence of multiple model instances, and, unknown nature of noise. The linear errors-in-variables (EIV) m...
SIAMCO
2008
13 years 4 months ago
2008
We investigate the asymptotic properties of a recursive kernel density estimator associated with the driven noise of a linear regression in adaptive tracking. We provide an almost ...
ML
2002
ACM
13 years 4 months ago
2002
ACM
Binningandtruncationofdataarecommonindataanalysisandmachinelearning.Thispaperaddresses the problem of fitting mixture densities to multivariate binned and truncated data. The EM ap...