[PD] ANN - Gesture Recognition Capabilities

Luigi Rensinghoff luigi.rensinghoff at freenet.de
Sun May 4 14:29:44 CEST 2008


Hi all

very interesting, really..

yet it does take me away more and more from my inital question ;-)

And a practical solution to implement some simplicistic gesture  
recognition in PD..

..and wait for the summer, when the PD bindings are ready...

I hope there will be some creative, artisitic examples then..

Best Regards


Luigi



Am 04.05.2008 um 13:59 schrieb Georg Holzmann:

> Hallo!
>
>> Hm. You can incorporate changes over time using a standard  
>> feedforward
>> ANN by wrapping your time-ordered vectors over a given time period  
>> into
>> a single input vector and increasing the number of inputs to the  
>> network
>> accordingly. But of course this introduces latency and other problems
>> (e.g. it could massively increase the number of training examples
>> required).
>>
>> Pd has the ann_td external, which provides a 'time delay' neural  
>> network
>> which I believe incorporates time using a method similar to that
>> described above.
>
> Yes of course, one other possibility is to use time delayed neural
> networks ...
>
>>> For example a hidden markov model or echo state network (=  
>>> special kind
>>> of recurrent neural network) should work.
>>
>> I'm intrigued! Presumably these approaches avoid the latency  
>> problem by
>> maintaining the network's state? Are there other advantages --  
>> easier to
>> train?
>
> Hm ... I did not think about latency ... but if you do not process the
> data in blocks there should not be a significant latency (also for the
> time delay NN) ?
>
> However, the advantage of the echo state network is that training is
> linear and you cannot get in a suboptimal solution as with feedforward
> neural networks (where the error surface has multiple local minimas) -
> see for example http://www.scholarpedia.org/article/Echo_state_network
> for a short introduction.
> And it is recurrent - so in general more powerful ... from the link  
> above:
> "On a number of benchmark tasks, ESNs have starkly outperformed all
> other methods of nonlinear dynamical modelling"
>
> If you are interested, I implemented ESNs (with various extensions)  
> in a
> C++ library with python bindings: http:// 
> aureservoir.sourceforge.net/, a
> PD external will hopefully follow in summer ...
>
> LG
> Georg
>
>
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 >---------------------------------------<

Luigi Rensinghoff
luigi.rensinghoff at freenet.de
skype:gigischinke
ichat:gigicarlo




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