[gdal-dev] [RFC] [GDAL] Idea for GSoC, 2014

[Seth Price]

I have done something like this recently. You would be better off tearing out SURF & linking to OpenCV for all feature detection and extraction. Here is a link to the patch that OpenCV needs to support large & 16 bit imagery.

https://github.com/Itseez/opencv/pull/1932

~Seth

via iPhone

> On Mar 15, 2014, at 12:50 PM, Kshitij Kansal <kansal.k at gmail.com> wrote:
> 
> Hello Again,
> 
> @Dimitriy - Currently the GDALComputeMatchingPoints  is using the SimpleSurf algorithm for matching points. Are you proposing that, I should implement the BRISK and then provide user the option of using either this or SimpleSurf(already implemented)? 
> This is indeed a very interesting thought but the problem in this is that, the GDALComputeMatchingPoints is developed with respect to the correlator project and I feel that SimpleSurf algorithm implemented there won't work on my Automatic geo-referencer as I would be considering the Multispectral Imagery and Large Datasets which are not handled in the current implementation. So this will require modification to SimpleSurf as well.
> I hope I have made my doubt clear? Please convey your views on this.
> 
> @Chaitanya - In comparison to the SURF, BRISK can definitely handle the large imagery to great extent. But there is going to be some threshold upto which this algorithm will work because we must not forget that these algorithms are developed for Normal RGB images for Computer Vision related work and there usage to Remote Sensing requires some modification. I will try to look for this thing in more detail and then get back to you.
> 
> 
> Also, should I prepare my initial draft of proposal based this BRISK idea only? 
> I have already started work in this direction and will soon post it, for review.
> 
> With Regards,
> 
> Kshitij Kansal
> Lab For Spatial Informatics,
> IIIT Hyderabad
> 
> 
>> On Sat, Mar 15, 2014 at 12:29 AM, Chaitanya kumar CH <chaitanya.ch at gmail.com> wrote:
>> Kshitij,
>> 
>> What is the performance of the proposed algorithms for very large rasters? If one of them is good with large images that's a cleaner choice without all the workaround with scaling the rasters.
>> 
>> --
>> Best regards,
>> Chaitanya Kumar CH
>> 
>>> On 15-Mar-2014 12:22 am, "Dmitriy Baryshnikov" <bishop.dev at gmail.com> wrote:
>>> Hi,
>>> 
>>> I think we need to decide it here, not to create lot of proposals. The second idea is very interesting. Maybe it worth to create some common interface (or API) to add new methods BRISK, SURF, SIFT etc. 
>>> You can develop you realisation of BRISK and demonstrate how-to one can use it via such common interface.
>>> E.g. in GDALComputeMatchingPoints add enum for algorithms or use exist  papszOptions.
>>> Best regards,
>>>     Dmitry
>>> 14.03.2014 17:28, Kshitij Kansal пишет:
>>>> Hello everyone
>>>> 
>>>> Continuing the previous discussion, I would like to propose something and the community's suggestions are welcomed/needed. I can understand that this thread is a little old, so let me remind you that its regarding the automatic geo-referencer idea. The idea is also proposed on the GDAL ideas page (http://trac.osgeo.org/gdal/wiki/SummerOfCode). 
>>>> 
>>>> Based on the previous discussions, what came out was that we can improve the current implementation of SIMPLE SURF in GDAL which was developed as a part of 2012 GSOC GDAL Correlator project, to support large data and multi spectral imagery. And then apply this modified algorithm for the geo-reference purposes. Now I have been in touch with Chaitanya, who is willing to mentor this project, and there are some things on which we would like to know community's suggestions/response.
>>>> 
>>>> There are basically two things that can be done regarding this project:
>>>> 
>>>> 1. As mentioned above, we can modify the SIMPLE SURF algorithm and make it much better for the geo-reference purposes. Already, a lot had been discussed on this and we           have a fairly good idea about what is to be done.
>>>> 
>>>> 2. One more thing that can be done is that we can implement BRISK algorithm[1] instead of SURF along with the FLANN matcher for this purpose. What advantages this thing offers is that it is fairly fast and gives comparable outputs along with           that it works well with fairly large data sets. So we do not need to segment the imagery as we would have done in the case of SURF. Also added to this, this algorithm also has no patent issues. We had a lot of problem regarding patent issues in SIFT/SURF and we discussed them at length on the mailing list as well. 
>>>> 
>>>> One thing that I fell can be done is that  two proposal can be written, one for each and then community can decide accordingly which one is more useful. Or we can decide it here itself..? 
>>>> 
>>>> Kindly provide your valuable comments and suggestion..
>>>> 
>>>> With Regards,
>>>> 
>>>> Kshitij Kansal
>>>> Lab For Spatial Informatics,
>>>> IIIT Hyderabad
>>>> 
>>>> 1. http://www.robots.ox.ac.uk/~vgg/rg/papers/brisk.pdf
>>> 
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