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CVPR
2009
IEEE
17 years 2 months ago
Discriminatively Trained Particle Filters for Complex Multi-Object Tracking
This work presents a discriminative training method for particle filters in the context of multi-object tracking. We are motivated by the difficulty of hand-tuning the many mode...
Alan Fern, Robin Hess
CVPR
2009
IEEE
17 years 2 months ago
On the burstiness of visual elements
Burstiness, a phenomenon initially observed in text re- trieval, is the property that a given visual element appears more times in an image than a statistically independent mode...
Herve Jegou (INRIA), Matthijs Douze (INRIA), Corde...
CVPR
2005
IEEE
16 years 9 months ago
Using Particles to Track Varying Numbers of Interacting People
In this paper, we present a Bayesian framework for the fully automatic tracking of a variable number of interacting targets using a fixed camera. This framework uses a joint multi...
Kevin Smith, Daniel Gatica-Perez, Jean-Marc Odobez
CVPR
2008
IEEE
16 years 9 months ago
A recursive filter for linear systems on Riemannian manifolds
We present an online, recursive filtering technique to model linear dynamical systems that operate on the state space of symmetric positive definite matrices (tensors) that lie on...
Ambrish Tyagi, James W. Davis
ICIP
2007
IEEE
16 years 8 months ago
Multi-Modal Particle Filtering Tracking using Appearance, Motion and Audio Likelihoods
We propose a multi-modal object tracking algorithm that combines appearance, motion and audio information in a particle filter. The proposed tracker fuses at the likelihood level ...
Matteo Bregonzio, Murtaza Taj, Andrea Cavallaro