Publication

An acoustic multiple target tracker

Publications associées (34)

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We present a Bayesian inference for a three-dimensional hydrodynamic model of Lake Geneva with stochastic weather forcing and high-frequency observational datasets. This is achieved by coupling a Bayesian inference package, SPUX, with a hydrodynamics packa ...

COPERNICUS GESELLSCHAFT MBH2022

The use of a Bayesian filter (e.g., Kalman filter) for the fusion of information from satellite positioning and inertial navigation is a common approach in many applications, where the knowledge of position, velocity, and attitude in space are of great int ...

EPFL2019

Finite Particle Flow Simulation of Free Jet Deviation by Rotating Pelton Buckets

Christian Vessaz

The prediction of hydraulic machines performances is of high interest to manufacturers in today's highly competitive market for new development or refurbishment of hydraulic power plant. An accurate prediction of the machines performances by numerical simu ...

EPFL2015

In this paper we present a method for fusing optical flow and inertial measurements. To this end, we derive a novel visual error term which is better suited than the standard continuous epipolar constraint for extracting the information contained in the op ...

2014

Diffusion estimation over cooperative networks with missing data

Ali H. Sayed

In many fields, and especially in the medical and social sciences and in various recommender systems, data are often gathered through clinical studies or targeted surveys. Participants are generally reluctant to respond to all questions in a survey or they ...

IEEE2013

A Multiple Hypothesis Gaussian Mixture Filter for Acoustic Source Localization and Tracking

In this work, we address the problem of tracking an acoustic source based on measured time difference of arrivals (TDOAs). The classical solution to this problem consists in using a detector, which estimates the TDOA for each microphone pair, and then appl ...

Idiap2012

A Multiple Hypothesis Gaussian Mixture Filter for Acoustic Source Localization and Tracking

In this work, we address the problem of tracking an acoustic source based on measured time differences of arrival (TDOA). The classical solution to this problem consists in using a detector, which estimates the TDOA for each microphone pair, and then apply ...

2012

Real time multi-object tracking using multiple cameras

Michail Zervos

We build a real-time multi-people tracker, which is based on the Kalman Filter. The input to the software is a Probabilistic Occupancy Map of the observed area. The main goal of the project is to incorporate this tracker to the real-time detection software ...

2012

Endothelial shear stress from large-scale blood flow simulations

Efthimios Kaxiras

We discuss the optimal evaluation of endothelial shear stress for real-life case studies based on anatomic data acquisition. The fluid dynamic simulations require smoothing of the geometric dataset to avoid major artefacts in the flow patterns, especially ...

2011

Diffusion Strategies for Distributed Kalman Filtering and Smoothing

Ali H. Sayed

We study the problem of distributed Kalman filtering and smoothing, where a set of nodes is required to estimate the state of a linear dynamic system from in a collaborative manner. Our focus is on diffusion strategies, where nodes communicate with their d ...

IEEE2010