Distance Estimation

[Chris Spencer]

Thanks, that's what I was looking for.

On Thu, Sep 1, 2016 at 3:29 AM, Emmanuelle Gouillart <
emmanuelle.gouillart at nsup.org> wrote:

> Hi Chris,
>
> the short version is no, there is no function in scikit-image that can do
> what the Stanford paper does. However, you can find some useful building
> blocks in scikit-image and scikit-learn, that you can put together to
> build your own version of the algorithm (from what I figured out after
> a quick reading of
> http://www.cs.cornell.edu/~asaxena/reconstruction3d/
> saxena_iccv_3drr07_learning3d.pdf)
>
> - Felzenswalb superpixels are available in skimage.segmentation
>   (http://scikit-image.org/docs/dev/auto_examples/segmentation/plot_
> segmentations.html)
> - Local features can be computed using several functions of scikit-image,
>   such as color transforms (color.ycbcr) and edge filters
> (filters.sobel_h, filters.sobel_v, ...)
> - A logistic regression algorithm is available in scikit-learn
>   (http://scikit-learn.org/stable/modules/generated/sklearn.linear_model.
> LogisticRegression.html)
>
> The trickiest part to code would be the MAP inference on the MRF, where I
> guess you would have to code it yourself (I think).
>
> So, it is feasible to assemble these different blocks, but it's not a
> small project either.
>
> As for other libraries, I'm afraid nothing comes to my mind. OpenCV does
> have a depth estimation function, but only from stereo images.
>
> Hope this helps,
> Emma
>
>
> On Wed, Aug 31, 2016 at 09:30:20PM -0400, Chris Spencer wrote:
> > Essentially, what's described here:
>
> > http://www.cs.cornell.edu/~asaxena/learningdepth/
>
> > On Wed, Aug 31, 2016 at 9:29 PM, Chris Spencer <chrisspen at gmail.com>
> wrote:
>
> >     Given a JPG image of a scene, convert that into a depth map, where
> each
> >     pixel is associated with a discrete distance estimate.
>
> >     On Wed, Aug 31, 2016 at 7:12 PM, Stefan van der Walt <
> stefanv at berkeley.edu>
> >     wrote:
>
> >         Hi Chris
>
> >         On Sun, Aug 28, 2016, at 17:31, Chris Spencer wrote:
> >         > Is there any algorithm in scikit-image that I could use to
> train a
> >         predictor that could estimate the distance at each pixel in an
> image?
>
> >         > I've gone through all the examples, and none of them seemed to
> >         directly apply. The image segmentation example seemed to be the
> >         closest, but that didn't use supervised learning, so I wasn't
> sure how
> >         I could adapt it's code.
>
> >         Could you explain what you mean by "estimate the distance"?
>
> >         Stéfan
>
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