Re: [Bayes++] Observation model for SIR scheme

[Nicola B. <nb...@es...>]

Hello,
In the SIR_kalman_scheme, is it possible I have several weights much bigger 
that 1? If not, which one could be the problem?
Thanks.

Nicola


On Sunday 19 Nov 2006 17:49, Nicola Bellotto wrote:
> Steven,
>
> Thanks for your reply. I fixed variance and number of samples also in my
> model and now there are no more exceptions indeed.
> As you said, unfortunately the SIR_scheme seems to be more sensitive to the
> model and this might be a big problem for me, since I am tracking humans
> for which a good motion model does not exist in general (although UKF seems
> to perform not too bad).
> I read some authors (Arulampalam et al.,  A tutorial on particle filters
> for online nonlinear/non-GaussianBayesian tracking, 2002) suggest
> Systematic Resampling, which is already implemented in your library indeed.
> What do you think?
> Also, I was wondering if the SIR_kalman_scheme is basically just a SIR
> filter providing the first two moments, 'x' and 'X', or something more
> performant (I saw for example that it has a different roughening
> procedure).
>
> Regards,
>
> Nicola
>
> On Saturday 18 Nov 2006 19:20, Michael Stevens wrote:
> > Nicola,
> >
> > On Saturday, 18. November 2006 15:47, Nicola Bellotto wrote:
> > > Steven,
> > >
> > > I modified my model inheriting from Likelihood_observe_model and
> > > copying the likelihood function code, but I had continuosly exceptions
> > > like "Roughening X not PSD" or "zero cumulative weight sum".
> > > So I went back to the simplest example, the PV_SIR.cpp, and modified
> > > just a little the observation model multiplying z_pred[0] and Hx(0,0)
> > > by 2 (see attached file). This caused again a "zero cumulative weight
> > > sum" exception. I looked through the library's code but I could not
> > > really understand the reason of the problem. What am I doing wrong?
> >
> > I took a quick look at this because I was fearing a bug. Lucky for me the
> > problem is with you small but significant change!
> >
> > Both the exceptions occur when the the SIR cannot solve the problem. As
> > you found this is quite easy to achive.
> >
> > "zero cumulative weight sum" occurs when the Likelihoods computed for all
> > the samples are zero.  When you doubled z_pred and Hx you omited to
> > double the true observation at line 199 in PV_SIR.cpp. Because the
> > position is 1000 this meant that the observation was 2*1000-1000 away
> > from the true. With an position variance of just 1, something 1000 away
> > is very very unlikely. In fact the likeilhood computed is 0!
> >
> > You should also note that the SIR_scheme is only constructed with 10
> > samples. This is very few and can also very quickly lead to on 1 sample
> > being chosen in many situations. This can lead to the "Roughening X not
> > PSD" exception. In practice you will usualy need more particles. Even
> > then, the standard SIR is very poor at solving problem if the prediction
> > is far away from the observation.
> >
> > Michael

-- 
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Nicola Bellotto
University of Essex
Department of Computer Science
Wivenhoe Park
Colchester CO4 3SQ
United Kingdom

Room: 1N1.2.8
Tel. +44 (0)1206 874094
URL: http://privatewww.essex.ac.uk/~nbello
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-- 
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Nicola Bellotto
University of Essex
Department of Computer Science
Wivenhoe Park
Colchester CO4 3SQ
United Kingdom

Room: 1N1.2.8
Tel. +44 (0)1206 874094
URL: http://privatewww.essex.ac.uk/~nbello
------------------------------------------