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Calibration-Free Eye Gaze Direction Detection with Gaussian Processes

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Recognizing Human Visual Focus of Attention from Head Pose in Meetings

Jean-Marc Odobez, Silèye Oumar Ba

We address the problem of recognizing the visual focus of attention (VFOA) of meeting participants based on their head pose. To this end, the head pose observations are modeled using a Gaussian Mixture Model (GMM) or a Hidden Markov Model (HMM) whose hidde ...

2009

Information Consistency of Nonparametric Gaussian Process Methods

Matthias Seeger

Bayesian nonparametric models are widely and successfully used for statistical prediction. While posterior consistency properties are well studied in quite general settings, results have been proved using abstract concepts such as metric entropy, and they ...

Institute of Electrical and Electronics Engineers2008

Joint head tracking and pose estimation for visual focus of attention recognition

Silèye Oumar Ba

During the last two decades, computer science what are the ability to give to provide to machines in order to give them the ability to understand human behavior. One of them which is an important key to understand human behaviors, is the visual focus of at ...

EPFL2007

Joint Head Tracking and Pose Estimation for Visual Focus of Attention Recognition

Silèye Oumar Ba

École Polytechnique Fédérale de Lausanne2007

Fast Gaussian Process Regression Using KD-Trees

Matthias Seeger

The computation required for Gaussian process regression with n training examples is about O(n^3) during training and O(n) for each prediction. This makes Gaussian process regression too slow for large datasets. In this paper, we present a fast approximati ...

2006

Worst-Case Bounds for Gaussian Process Models

Matthias Seeger

We present a competitive analysis of some non-parametric Bayesian algorithms in a worst-case online learning setting, where no probabilistic assumptions about the generation of the data are made. We consider models which use a Gaussian process prior (over ...

2006

Mean-Square Performance of a Family of Affine Projection Algorithms

Ali H. Sayed

Affine projection algorithms are useful adaptive filters whose main purpose is to speed the convergence of LMS-type filters. Most analytical results on affine projection algorithms assume special regression models or Gaussian regression data. The available ...

Institute of Electrical and Electronics Engineers2004

Gaussian Processes for Machine Learning

Matthias Seeger

Gaussian processes (GPs) are natural generalisations of multivariate Gaussian random variables to infinite (countably or continuous) index sets. GPs have been applied in a large number of fields to a diverse range of ends, and very many deep theoretical an ...

World Scientific Publishing2004

Transient behavior of affine projection algorithms

Ali H. Sayed

Most analytical results on affine projection algorithms assume special regression models or Gaussian regression data. The available analyses also treat different affine projection filters separately. This paper provides a unified treatment of the transient ...

2003

Transient analysis of adaptive filters with error nonlinearities

Ali H. Sayed

The paper develops a unified approach to the transient analysis of adaptive filters with error nonlinearities. In addition to deriving earlier results in a unified manner, the approach also leads to new performance results without restricting the regressio ...

IEEE2003