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Motion likelihood and proposal modeling in Model-Based Stochastic Tracking

Publications associées (45)

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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

Motion models for robust 3D human body tracking

Raquel Urtasun

In this work, we propose new ways to learn pose and motion priors models and show that they can be used to increase the performance of 3D body tracking algorithms, resulting in very realistic motions under very challenging conditions. We first explored an ...

EPFL2006

Ultrawide Bandwidth Signals as Shot-Noise: a Unifying Approach

Andrea Ridolfi

This paper presents general methods for obtaining power spectra of a large class of signals and random fields driven by an underlying point processes, in particular spatial shot noises with random impulse response and arbitrary basic stationary point proce ...

2005

3D Position Tracking in Challenging Terrain

Roland Siegwart, Pierre Lamon

The intent of this paper is to show how the accuracy of 3D position tracking can be improved by considering rover locomotion in rough terrain as a holistic problem. An appropriate locomotion concept endowed with a controller min- imizing slip improves the ...

2005

A Video Database for Head Pose Tracking Evaluation

Jean-Marc Odobez, Silèye Oumar Ba

This document describes our work to provide a video database, of people in real situations with their head pose continuously annotated through time. The head poses were annotated using a magnetic 3d location and orientation tracker, the flock of bird. The ...

IDIAP2005

Embedding motion in model-based stochastic tracking

Daniel Gatica-Perez, Jean-Marc Odobez

2004

3D Tracking for Gait Characterization and Recognition

Pascal Fua, Raquel Urtasun

We propose an approach to gait analysis that relies on fitting 3--D temporal motion models to synchronized video sequences. These models allow us not only to track but also to recover motion parameters that can be used to recognize people and characterize ...

2004

3D human body tracking using deterministic temporal motion models

Pascal Fua, Raquel Urtasun

There has been much effort invested in increasing the robustness of human body tracking by incorporating motion models. Most approaches are probabilistic in nature and seek to avoid becoming trapped into local minima by considering multiple hypotheses, whi ...

Springer2004

Hierarchical Implicit Surface Joint Limits for Human Body Tracking

Pascal Fua, Raquel Urtasun, Lorna Herda

To increase the reliability of existing human motion tracking algorithms, we propose a method for imposing limits on the underlying hierarchical joint structures in a way that is true to life. Unlike most existing approaches, we explicitly represent depend ...

2004

A probabilistic framework for joint head tracking and pose estimation

Jean-Marc Odobez, Silèye Oumar Ba

Head Tracking and pose estimation are usually considered as two sequential and separate problems: pose is estimated on the head patch provided by a tracking module. However, precision in head pose estimation is dependent on tracking accuracy which itself c ...

2004