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ICASSP
2011
IEEE
14 years 4 months ago
Non-parametric bayesian measurement noise density estimation in non-linear filtering
In this study, we investigate online Bayesian estimation of the measurement noise density of a given state space model using particle filters and Dirichlet process mixtures. Diri...
Emre Özkan, Saikat Saha, Fredrik Gustafsson, ...
117
Voted
ECCV
2004
Springer
16 years 2 months ago
Optimal Importance Sampling for Tracking in Image Sequences: Application to Point Tracking
Abstract. In this paper, we propose a particle filtering approach for tracking applications in image sequences. The system we propose combines a measurement equation and a dynamic ...
Étienne Mémin, Elise Arnaud
116
Voted
ECCV
2006
Springer
16 years 2 months ago
Random Walks, Constrained Multiple Hypothesis Testing and Image Enhancement
Image restoration is a keen problem of low level vision. In this paper, we propose a novel - assumption-free on the noise model - technique based on random walks for image enhancem...
Noura Azzabou, Nikos Paragios, Frederic Guichard
126
Voted
ECCV
2006
Springer
15 years 4 months ago
A Rao-Blackwellized Parts-Constellation Tracker
We present a method for efficiently tracking objects represented as constellations of parts by integrating out the shape of the model. Parts-based models have been successfully ap...
Grant Schindler, Frank Dellaert
91
Voted
ICCV
2009
IEEE
1068views Computer Vision» more  ICCV 2009»
16 years 5 months ago
Illumination Aware MCMC Particle Filter for Long-Term Outdoor Multi-Object Simultaneous Tracking and Classification
This paper addresses real-time automatic visual tracking, labeling and classification of a variable number of objects such as pedestrians or/and vehicles, under timevarying illu...
Franc¸ois Bardet, Thierry Chateau, Datta Ramadasa...