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ParticleFilterTrackerwithIsomap
- We propose a novel approach for head tracking, which combines particle filters with Isomap. The particle filter works on the low-dimensional embedding of training images. It indexes into the Isomap with its state variables to find the closest templat
OnusingLikelihood-adjustedProposalsinParticleFilte
- An unsatisfactory property of particle filters is that they may become inefficient when the observation noise is low. In this paper we consider a simple-to-implement particle filter, called ‘LIS-based particle filter’, whose aim is to overcome
AMODIFIEDRAO-BLACKWELLISEDPARTICLEFILTER
- Rao-Blackwellised Particle Filters (RBPFs) are a class of Particle Filters (PFs) that exploit conditional dependencies between parts of the state to estimate. By doing so, RBPFs can improve the estimation quality while also reducing the overall
Tracking_object_
- Tracking source: Particle filters are now established as the most popular method for visual tracking. Within this framework, it is generally assumed that the data are temporally independent given the sequence of object states. In this paper, we arg
particlefilters.pdf
- A short tutorial on Particle Filters.
OLT
- We present a parallel implementation of a histogram-based particle filter for object tracking on smart cameras based on SIMD processors. We specifically focus on parallel computation of the particle weights and parallel construction of the featur