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Conference Papers Year : 2009

M2SIR : A multi modal sequential importance resampling algorithm for particle filters

Abstract

We present a multi modal sequential importance resampling particle filter algorithm for object tracking. We consider a hidden state sequence linked to several observation sequences given by different sensors. In a particle filter based framework, each sensor provides a likelihood (weight) associated to each particle and simple rules are applied to merge the different weights such as addition or product. We propose an original algorithm based on likelihood ratios to merge the observations within the sampling step. The algorithm is compared with classic fusion operations on toy examples. Moreover, we show that the method gives satisfactory results on a real vehicle tracking application.
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Dates and versions

hal-00421055 , version 1 (30-09-2009)

Identifiers

  • HAL Id : hal-00421055 , version 1

Cite

Yann Goyat, Thierry Chateau, Laurent Trassoudaine. M2SIR : A multi modal sequential importance resampling algorithm for particle filters. IEEE International Conference on Image Processing, Nov 2009, France. 4p. ⟨hal-00421055⟩
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