%0 Conference Paper %1 torma2005 %A Torma, P. %A Szepesvári, Cs. %B 4th International Symposium on Image and Signal Processing and Analysis %D 2005 %K application filtering, particle theory, vision, %P 1--2 %T On using Likelihood-adjusted Proposals in Particle Filtering: Local Importance Sampling %X 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 the above mentioned weakness. LIS-based particle filters sample the particles in a two-stage process that uses information of the most recent observation, too. Experiments with the standard bearings-only tracking problem indicate that the proposed new particle filter method is indeed a viable alternative to other methods.

@inproceedings{torma2005, abstract = {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 the above mentioned weakness. LIS-based particle filters sample the particles in a two-stage process that uses information of the most recent observation, too. Experiments with the standard bearings-only tracking problem indicate that the proposed new particle filter method is indeed a viable alternative to other methods.}, added-at = {2020-03-17T03:03:01.000+0100}, author = {Torma, P. and Szepesv{\'a}ri, {Cs}.}, biburl = {https://www.bibsonomy.org/bibtex/2b417fe0c37856cf1a5e0c5792fc85793/csaba}, booktitle = {4th International Symposium on Image and Signal Processing and Analysis}, date-modified = {2010-11-25 00:00:51 -0700}, interhash = {649d90cbb6dc7a02679057f42ce998ae}, intrahash = {b417fe0c37856cf1a5e0c5792fc85793}, keywords = {application filtering, particle theory, vision,}, owner = {Beata}, pages = {1--2}, pdf = {papers/torma-ispa2005.pdf}, timestamp = {2020-03-17T03:03:01.000+0100}, title = {On using Likelihood-adjusted Proposals in Particle Filtering: Local Importance Sampling}, year = 2005 }