Concept

Markov random field

Related publications (119)

Exploring Contextual Information in a Layered Framework for Group Action Recognition

Daniel Gatica-Perez, Samy Bengio, Dong Zhang

Contextual information is important for sequence modeling. Hidden Markov Models (HMMs) and extensions, which have been widely used for sequence modeling, make simplifying, often unrealistic assumptions on the conditional independence of observations given ...

2006

Exploring Contextual Information in a Layered Framework for Group Action Recognition

Daniel Gatica-Perez, Samy Bengio, Dong Zhang

IDIAP2006

Kernel Methods for Melanoma Recognition

Barbara Caputo, Tatiana Tommasi

Skin cancer is a spreading disease in the western world. Early detection and treatment are crucial for improving the patient survival rate. In this paper we present two algorithms for computer assisted diagnosis of melanomas. The first is the support vecto ...

2006

Integrating co-occurrence and spatial contexts on patch-based scene segmentation

Daniel Gatica-Perez, Jean-Marc Odobez, Florent Monay Michaud, Pedro Manuel Da Silva Quelhas

We present a novel approach for contextual segmentation of complex visual scenes, based on the use of bags of local invariant features (visterms) and probabilistic aspect models. Our approach uses context in two ways: (1) by using the fact that specific le ...

2006

Efficient Nonparametric Bayesian Modelling with Sparse Gaussian Process Approximations

Matthias Seeger

Sparse approximations to Bayesian inference for nonparametric Gaussian Process models scale linearly in the number of training points, allowing for the application of powerful kernel-based models to large datasets. We present a general framework based on t ...

2006

Melanoma Recognition Using Representative and Discriminative Kernel Classifiers

Barbara Caputo, Tatiana Tommasi

Malignant melanoma is the most deadly for of skin lesion. Early diagnosis is of critical importance to patient survival. Visual recognition algorithms could potentially be of great help for physicians in a computer assisted diagnosis system. Previous work ...

2006

Second-order hyperbolic S.P.D.E.'s driven by homogeneous Gaussian noise on a hyperplane

Robert Dalang, Olivier Lévêque

We study a class of hyperbolic stochastic partial di®erential equations in Euclidean space, that includes the wave equation and the telegraph equation, driven by Gaussian noise concentrated on a hyperplane. The noise is assumed to be white in time but spat ...

2006

Point Similarity Measures Based on MRF Modeling of Difference Images for Spline-Based 2D-3D Rigid Registration of x-Ray Fluoroscopy to CT Images

Michaël Unser, Philippe Thévenaz, Xiuwei Zhang

One of the main factors that affect the accuracy of intensity-based registration of two-dimensional (2D) X-ray fluoroscopy to three-dimensional (3D) CT data is the similarity measure, which is a criterion function that is used in the registration procedure ...

Springer2006

Percolation in the signal to interference ratio graph

Patrick Thiran, Nicolas Macris, Olivier Dousse

Continuum percolation models in which pairs of points of a two-dimensional Poisson point process are connected if they are within some range to each other have been extensively studied. This paper considers a variation in which a connection between two poi ...

2006

Learning influence among interacting Markov chains

Daniel Gatica-Perez, Samy Bengio, Dong Zhang

We present a model that learns the influence of interacting Markov chains within a team. The proposed model is a dynamic Bayesian network (DBN) with a two-level structure: individual-level and group-level. Individual level models actions of each player, an ...

IDIAP2005

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