seeking advice on HoG applicability

[Lisa Torrey]

Thank you! The clustering step is definitely what was missing from my 
understanding of the "bag of words" approach.

-Lisa


On Thursday, July 18, 2013 4:14:46 AM UTC-4, Anders Boesen Lindbo Larsen 
wrote:
>
> I attach this mail correspondence as it may be relevant for others.
>
> Stefan: Do you think a bag of words implementation would fit into 
> scikit-image? I have some code that I would be happy to polish and 
> contribute. The main problem is that bag-of-words rely on a k-means 
> clustering method which I would prefer to import from scikit-learn because 
> the one from scipy is slow for a large number of samples. It is my 
> impression that scikit-image tries to stay independent of scikit-learn.
>
> Cheers,
> Anders
>
>
> ---------- Forwarded message ----------
> From: Anders Boesen Lindbo Larsen <ab... at dtu.dk <javascript:>>
> Date: Thu, Jul 18, 2013 at 10:00 AM
> Subject: Re: about DAISY
> To: Lisa Torrey <lto... at stlawu.edu <javascript:>>
>
>
> Hi Lisa,
>
> Cool problem; I have also read about it on the scikits-image mailing list.
>
> I would start out with a simple approach called 'bag of words' (aka.
> 'bag of features'). First, you sample a bunch of overlapping DAISY
> features for a representative set of training images and perform a
> clustering (e.g. k-means with k=1000) of these descriptors. You can
> think of the cluster centers (aka. visual words) as a vocabulary. An
> image can now be described by extracting DAISY features and mapping
> each feature to its nearest cluster center in the vocabulary. By
> counting the number of occurrences of each visual word you end up with
> a histogram which you can use for comparing images.
> Bag of words models have shown quite successful for many flavors of
> visual recognition because they are able to capture texture and image
> structure in a generic manner. That is, you don't have to engineer the
> model much to make it fit your problem.
>
> I'd be happy to help you if you have further questions.
>
> Best,
> Anders
>
> On Tue, Jul 16, 2013 at 6:02 PM, Lisa Torrey <lto... at stlawu.edu<javascript:>> 
> wrote:
> > Hi Anders -
> >
> > I'm trying to determine if DAISY descriptors might be suitable for a 
> problem
> > I'm working on. I see that you have some expertise in this area, since 
> you
> > contributed the DAISY code to scikit-image, and I'm wondering if you'd be
> > willing to let me know your thoughts.
> >
> > I'm mainly trying to understand if DAISY descriptors could be effectively
> > used as features in a binary classification problem where the two image
> > classes have a lot of internal variation.
> >
> > The two classes I'm working with are two types of moss. Type 1 is 
> typically
> > a stalk with leaves on it. Type 2 is typically a stalk with some branches
> > coming off it, and leaves on the branches. But there's quite a bit of 
> visual
> > diversity within these types. A type represents a group of moss species 
> that
> > can look surprisingly different from each other. On top of that, the 
> images
> > I've got have no common size or orientation.
> >
> > If you have any thoughts, I'd love to hear them. I can share some 
> examples
> > of moss images if you're curious, but even a gut reaction would be 
> helpful.
> >
> > -Lisa
> >
>
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