[OpenDroneMap-users] "bowl" effect
Stephen Mather
stephen at smathermather.com
Mon Oct 5 19:27:52 PDT 2015
Hi Anna,
Good news. I've been bad here and cc'd Pau who an hopefully answer your
question on parameters.
That said, if you have all the parameters, is there any reason to not
undistort before feeding into ODM?
Cheers,
Best,
Steve
On Sun, Oct 4, 2015 at 6:04 PM, Anna Petrášová <kratochanna at gmail.com>
wrote:
>
> 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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