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An Implicit Motion Likelihood for Tracking with Particle Filters

Publications associées (74)

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Feature point tracking combining the Interacting Multiple Model filter and an efficient assignment algorithm

Touradj Ebrahimi, Yousri Abdeljaoued

An algorithm for feature point tracking is proposed. The Interacting Multiple Model (IMM) filter is used to estimate the state of a feature point. The problem of data association, i.e. establishing which feature point to use in the state estimator, is solv ...

2007

Target tracking using a joint acoustic video system

Volkan Cevher

In this paper, we present a particle filter that exploits multi modal information for robust target tracking. We demonstrate a Bayesian framework for combining acoustic and video information using a state space approach. A proposal strategy for joint acous ...

2007

Embedding Motion in Model-Based Stochastic Tracking

Daniel Gatica-Perez, Jean-Marc Odobez, Silèye Oumar Ba

Particle filtering (PF) is now established as one of the most popular methods for visual tracking. Within this framework, two assumptions are generally made. The first is that the data are temporally independent given the sequence of object states, and the ...

2006

A range-only multiple target particle filter tracker

Volkan Cevher

We propose a particle filter tracker to track multiple maneuvering targets using a batch of range measurements. The state update is formulated through a locally linear motion model and the observability of the state vector is proved using geometrical argum ...

2006

Origami, Brettrippen und Reibschweissen

Yves Weinand

Seit nunmehr 18 Monaten hat der Lehrstuhl für Holzkonstruktionen der EPFL, der 27 Jahre lang von Prof. Natterer geführt wurde, einen neuen Leiter und damit eine neue Forschungsrichtung: "New Modeling" - neue Wege der Formfindung durch interdisziplinäre Zus ...

2006

Hybrid Tracking for Augmented Reality

Touradj Ebrahimi

Accurate registration between real and virtual objects is critical for Augmented Reality (AR) applications. State of the art shows that no tracking device is individually adequate. We present a data fusion framework that combines orientation measurements o ...

2005

On the optimal density for real-time data gathering of spatio-temporal processes in sensor networks

Martin Vetterli, Razvan Cristescu

We consider sensor networks that measure spatio-temporal correlated processes. An important task in such settings is the reconstruction at a certain node, called the sink, of the data at all points of the field. We consider scenarios where data is time cri ...

IEEE2005

Tracking Video Objects in Cluttered Background

Touradj Ebrahimi

We present an algorithm for tracking video object which is based on an hybrid strategy. This strategy uses both object and region information to solve the correspondence problem. Low level descriptors are exploited to track objects regions and to cope wit ...

2005

Embedding motion in model-based stochastic tracking

Daniel Gatica-Perez, Jean-Marc Odobez

2004

General state-space models

Thomas Gsponer

In time series analysis state-space models provide a wide and flexible class. The basic idea is to describe an unobservable phenomenon of interest on the basis of noisy data. The first constituent of such a model is the so-called state equation, which char ...

EPFL2004