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» Evaluation of Robust Fitting Based Detection
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ECCV
2004
Springer
14 years 6 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 4 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 6 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
13 years 11 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
13 years 11 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...