Accelerating Particle filter using multiscale methods

Yaniv Shmueli, Gil Shabat, Amit Bermanis, Amir Averbuch

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We present a method that accelerates the Particle Filter computation. Particle Filter is a powerful method for tracking the state of a target based on non-linear observations. Unlike the conventional way of calculating weights over all particles in each run, we sample a small subset of the particles using matrix decomposition methods, followed by a novel function extension algorithm to recover the density function of all particles. This significantly reduces the computational load where the measurement computation is substantial, as often happens, for example, when tracking targets in videos. We demonstrate our method on both simulated data and real data (videos).

Original languageEnglish
Title of host publication2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2012
DOIs
StatePublished - 2012
Event2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2012 - Eilat, Israel
Duration: 14 Nov 201217 Nov 2012

Publication series

Name2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2012

Conference

Conference2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2012
Country/TerritoryIsrael
CityEilat
Period14/11/1217/11/12

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