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ICPR
2008
IEEE
14 years 5 months ago
Comparison of Particle Swarm Optimization and Genetic Algorithm for HMM training
Hidden Markov Model (HMM) is the dominant technology in speech recognition. The problem of optimizing model parameters is of great interest to the researchers in this area. The Ba...
Fengqin Yang, Changhai Zhang, Tieli Sun
CVPR
2009
IEEE
15 years 5 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
2005
IEEE
15 years 23 days ago
Appearance-Guided Particle Filtering for Articulated Hand Tracking
We propose a model-based tracking method, called appearance-guided particle filtering (AGPF), which integrates both sequential motion transition information and appearance informa...
Wen-Yan Chang, Chu-Song Chen, Yi-Ping Hung
CVPR
2005
IEEE
15 years 23 days 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
ICIP
2007
IEEE
15 years 13 days 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