Sciweavers

Share
ICCV
2011
IEEE
8 years 5 months ago
A Nonparametric Riemannian Framework on Tensor Field with Application to Foreground Segmentation
Background modelling on tensor field has recently been proposed for foreground detection tasks. Taking into account the Riemannian structure of the tensor manifold, recent resear...
Rui Caseiro, João F. Henriques, Pedro Martins, Jo...
CVIU
2011
8 years 9 months ago
Single and sparse view 3D reconstruction by learning shape priors
In this paper, we aim to reconstruct free-form 3D models from only one or few silhouettes by learning the prior knowledge of a specific class of objects. Instead of heuristically...
Yu Chen, Roberto Cipolla
SYNTHESE
2011
72views more  SYNTHESE 2011»
9 years 25 days ago
Science without (parametric) models: the case of bootstrap resampling
Scientific and statistical inferences build heavily on explicit, parametric models, and often with good reasons. However, the limited scope of parametric models and the increasin...
Jan Sprenger
MA
2010
Springer
143views Communications» more  MA 2010»
9 years 4 months ago
The pairwise beta distribution: A flexible parametric multivariate model for extremes
We present a new parametric model for the angular measure of a multivariate extreme value distribution. Unlike many parametric models that are limited to the bivariate case, the ...
Daniel Cooley, Richard A. Davis, Philippe Naveau
PE
2007
Springer
131views Optimization» more  PE 2007»
9 years 5 months ago
Moment estimation in delay tomography with spatial dependence
Parametric models for estimating network link delays with incomplete data that incorporate spatial correlation are formulated. Fast numerical methods for estimation of parameters ...
Ian H. Dinwoodie, Eric A. Vance
DAGM
2010
Springer
9 years 6 months ago
Complex Motion Models for Simple Optical Flow Estimation
The selection of an optical flow method is mostly a choice from among accuracy, efficiency and ease of implementation. While variational approaches tend to be more accurate than lo...
Claudia Nieuwenhuis, Daniel Kondermann, Christoph ...
DATE
2005
IEEE
128views Hardware» more  DATE 2005»
9 years 11 months ago
Modeling Interconnect Variability Using Efficient Parametric Model Order Reduction
Assessing IC manufacturing process fluctuations and their impacts on IC interconnect performance has become unavoidable for modern DSM designs. However, the construction of parame...
Peng Li, Frank Liu, Xin Li, Lawrence T. Pileggi, S...
HICSS
2006
IEEE
114views Biometrics» more  HICSS 2006»
9 years 12 months ago
New Probabilistic Method for Estimation of Equipment Failures and Development of Replacement Strategies
When large amount of statistical information about power system component failure rate is available, statistical parametric models can be developed for predictive maintenance. Oft...
Miroslav Begovic, Petar M. Djuric, Joshua Perkel, ...
ECCV
2004
Springer
10 years 7 months ago
A Robust Probabilistic Estimation Framework for Parametric Image Models
Models of spatial variation in images are central to a large number of low-level computer vision problems including segmentation, registration, and 3D structure detection. Often, i...
Maneesh Kumar Singh, Himanshu Arora, Narendra Ahuj...
books