The benefits of down-sampling in the particle filter.
Fredrik GustafssonSaikat SahaUmut OrgunerPublished in: FUSION (2011)
Keyphrases
- particle filter
- sequential monte carlo
- monte carlo
- proposal distribution
- importance sampling
- markov chain monte carlo
- particle filtering
- object tracking
- visual tracking
- motion model
- state space
- likelihood function
- appearance model
- data association
- mean shift
- kalman filter
- robust tracking
- observation model
- bayesian inference
- state estimation
- face tracking
- multiple hypotheses
- robust visual tracking
- multiple objects
- multiple object tracking
- high dimensional state space
- tracking accuracy
- rao blackwellized particle filter
- random sampling
- sample size
- multiple hypothesis
- machine learning
- target tracking
- extended kalman filter
- parameter space
- markov chain
- probabilistic model
- feature space
- articulated body
- bayesian networks