[OpenDroneMap-users] "bowl" effect

[Anna Petrášová]

On Thu, Jun 25, 2015 at 11:04 PM, Stephen Mather <stephen at smathermather.com>
wrote:

> If memory serves, Anna has proper survey points, so Z is pretty good.
>
> Regarding the alternate branch -- there's nothing wrong with it, and
> it may be the FUTURE, but TBH, I haven't had a chance to test it
> properly... . I was hoping you'd try it, since you have such good
> secondary data to verify how it does... .
>
> Cheers,
> Best,
> Steve
>
>
>

Hi,

finally tested the OpenSfM now when it's merged. It gives better results in
terms of the bowl effect - there is still some, but not as huge (and it
seems faster). Does anyone know if I can pass calibration parameters of the
camera to OpenSfM? In the configuration file, there is:

radial_distorsion_k1_sd: 0.01 # The standard deviation of the first radial
distortion parameter (mean assumed to be 0)

but I have k1, not its standard deviation? Should I rather ask on the
mapillary forum?

Thanks,

Anna


>
>
>
> On Wed, Jun 24, 2015 at 2:20 AM, Alex Mandel <tech_dev at wildintellect.com>
> wrote:
> > On 06/22/2015 06:24 PM, Anna Petrášová wrote:
> >> On Mon, Jun 22, 2015 at 6:00 PM, Stephen Mather <
> stephen at smathermather.com>
> >> wrote:
> >>
> >>> Ah, ugly. Well, pretty really, but ugly from a data perspective. So
> >>> systematic bias in structure from motion is an issue with all systems,
> and
> >>> difficult to overcome with drone imagery in particular, if the drone is
> >>> flown in a single Z plane, particularly over relatively flat terrain.
> This
> >>> is an indictment of the data, just stating a known difficulty. This is
> why
> >>> balloon and kite flights, aside from areal coverage, are so pleasant to
> >>> process -- plenty of x, y, and z movement, so less chance for
> systematic
> >>> bias. I've been wondering if once a dataset like Open Terrain (a global
> >>> highest-available) is available, if it might be helpful for
> compensating
> >>> for bias in datasets, and also help with data classification pipelines
> that
> >>> can have separate meshing mechanisms for ground, vegetation, and human
> >>> structures.
> >>>
> >>
> >> I was thinking about compensating for the bias based on the lidar data I
> >> have, but I haven't tried it yet.
> >>
> >>>
> >>> That said, let's get a little more context on the dataset and
> processing
> >>> -- did you use ground control and if so, how was it distributed? It
> would
> >>> be interesting to know if you had ground control in the center of the
> >>> scene, if ODM is ignoring this extra info. Also, what kind of camera
> is it?
> >>> It is possible that the three parameter corrections that ODM is
> performing
> >>> are inadequate, and a 6-parameter model would be better.
> >>>
> >>
> >> There isn't really any gcp in the middle of it:
> >>
> https://drive.google.com/file/d/0B7CQoT4YE2mMNzJSbEZsaGtrZ3hnRUdPQ3VDbF9DS0o2SS1j/view?usp=sharing
> >>
> >> but how could the GCPs help? Georeferencing won't really change the
> shape,
> >> isn't it just rotation and translation?
> >>
> >
> > The ODM format for a GCP file is X,Y,Z so yes there is height data if
> > you are providing GCPs. Of course if the Z is provided from a standard
> > GPS unit that might not be super useful.
> >
> > -Alex
>
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