Concept

Kernel density estimation

Related publications (186)

Crowd Patches: Populating Large-Scale Virtual Environments for Real-Time Applications

Daniel Thalmann, Jonathan Maim, Barbara Yersin

Populating virtual environments (VEs) with large crowds is a subject that has been tackled for several years. Solutions have been proposed to offer realistic trajectories as well as interactivity, but limitations remain on the environment dimensions with r ...

2009

SURE-Based Non-Local Means

Dimitri Nestor Alice Van De Ville, Michel Kocher

Non-local means (NLM) provides a powerful framework for denoising. However, there are a few parameters of the algorithm-most notably, the width of the smoothing kernel-that are data-dependent and difficult to tune. Here, we propose to use Stein's unbiased ...

Institute of Electrical and Electronics Engineers2009

Nonlinear storage-discharge relations and catchment streamflow regimes

Andrea Rinaldo, Gianluca Botter

Nonlinear storage-discharge relations may explain important hydrologic features frequently observed under a variety of environmental conditions. In this paper the catchment dynamic storage problem is addressed by incorporating nonlinear storage-discharge r ...

American Geophysical Union2009

A Proposal for a Kernel-based Algorithm for Large Vocabulary Continuous Speech Recognition

We present a proposal of a kernel-based model for large vocabulary continuous speech recognizer. The continuous speech recognition is described as a problem of finding the best phoneme sequence and its best time span, where the phonemes are generated from ...

John Wiley and Sons2009

The Marr Wavelet Pyramid

Michaël Unser, Dimitri Nestor Alice Van De Ville

We introduce a new semi-orthogonal complex wavelet basis of

L _{ 2 }

(\mathbb{R} ^{ 2 }

). The basis functions are associated to the complex gradient-Laplace operator, which plays a central role in image processing. We define analytically a single- ...

IEEE2008

Redescending M-estimators

Stephan Morgenthaler

in finite sample studies redescending M-estimators outperform bounded M-estimators (see for example, Andrews et al. [1972. Robust Estimates of Location. Princeton University Press, Princeton]). Even though redescenders arise naturally out of the maximum li ...

Elsevier2008

A Discriminative Kernel-based Model to Rank Images from Text Queries

Samy Bengio, David Grangier

This paper introduces a discriminative model for the retrieval of images from text queries. Our approach formalizes the retrieval task as a ranking problem, and introduces a learning procedure optimizing a criterion related to the ranking performance. The ...

2008

Complex Wavelet Bases, Steerability, and the Marr-Like Pyramid

Michaël Unser, Dimitri Nestor Alice Van De Ville

Our aim in this paper is to tighten the link between wavelets, some classical image-processing operators, and David Marr's theory of early vision. The cornerstone of our approach is a new complex wavelet basis that behaves like a smoothed version of the Gr ...

Institute of Electrical and Electronics Engineers2008

Variational Segmentation using Fuzzy Region Competition and Local Non-Parametric Probability Density Functions

Jean-Philippe Thiran, Benoit Mory

We describe a novel variational segmentation algorithm designed to split an image in two regions based on their intensity distributions. A functional is proposed to integrate the probability density functions of both regions within the optimization process ...

2007

Cross-Validation Optimization for Large Scale Hierarchical Classification Kernel Methods

Matthias Seeger

We propose a highly efficient framework for kernel multi-class models with a large and structured set of classes. Kernel parameters are learned automatically by maximizing the cross-validation log likelihood, and predictive probabilities are estimated. We ...

2007

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The Marr Wavelet Pyramid

Michaël Unser, Dimitri Nestor Alice Van De Ville

We introduce a new semi-orthogonal complex wavelet basis of

L _{ 2 }

(\mathbb{R} ^{ 2 }

). The basis functions are associated to the complex gradient-Laplace operator, which plays a central role in image processing. We define analytically a single- ...

IEEE2008