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» Evaluation of Robust Fitting Based Detection
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ECCV
2004
Springer
14 years 8 months ago
Evaluation of Robust Fitting Based Detection
Low-level image processing algorithms generally provide noisy features that are far from being Gaussian. Medium-level tasks such as object detection must therefore be robust to out...
Sio-Song Ieng, Jean-Philippe Tarel, Pierre Charbon...
BMCBI
2006
187views more  BMCBI 2006»
13 years 7 months ago
Detecting outliers when fitting data with nonlinear regression - a new method based on robust nonlinear regression and the false
Background: Nonlinear regression, like linear regression, assumes that the scatter of data around the ideal curve follows a Gaussian or normal distribution. This assumption leads ...
Harvey J. Motulsky, Ronald E. Brown
ICPR
2008
IEEE
14 years 8 months ago
3D model based vehicle localization by optimizing local gradient based fitness evaluation
We address the problem of 3D model based vehicle localization in calibrated traffic scenes. A wireframe vehicle model is set up as prior information and an efficient local gradien...
Kaiqi Huang, Min Li, Tieniu Tan, Zhaoxiang Zhang
ICASSP
2008
IEEE
14 years 1 months 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
DAGM
2007
Springer
14 years 1 months ago
Learning Robust Objective Functions with Application to Face Model Fitting
Abstract. Model-based image interpretation extracts high-level information from images using a priori knowledge about the object of interest. The computational challenge is to dete...
Matthias Wimmer, Sylvia Pietzsch, Freek Stulp, Ber...