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IJCV
2000
133views more  IJCV 2000»
13 years 5 months ago
Heteroscedastic Regression in Computer Vision: Problems with Bilinear Constraint
We present an algorithm to estimate the parameters of a linear model in the presence of heteroscedastic noise, i.e., each data point having a different covariance matrix. The algor...
Yoram Leedan, Peter Meer
CVPR
2011
IEEE
13 years 2 months ago
Saliency Estimation Using a Non-Parametric Low-Level Vision Model
Many successful models for predicting attention in a scene involve three main steps: convolution with a set of filters, a center-surround mechanism and spatial pooling to constru...
Naila Murray, Maria Vanrell, Xavier Otazu, C. Alej...
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...
CVPR
2006
IEEE
13 years 11 months ago
New Method of Probability Density Estimation with Application to Mutual Information Based Image Registration
We present a new, robust and computationally efficient method for estimating the probability density of the intensity values in an image. Our approach makes use of a continuous r...
Ajit Rajwade, Arunava Banerjee, Anand Rangarajan
IPMI
2009
Springer
14 years 6 months ago
Estimation of Inferential Uncertainty in Assessing Expert Segmentation Performance from STAPLE
The evaluation of the quality of segmentations of an image, and the assessment of intra- and inter-expert variability in segmentation performance, has long been recognized as a dic...
Olivier Commowick, Simon K. Warfield