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Denser 3D Point Clouds in OpenSfM

blog.mapillary.com

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Re: Denser 3D Point Clouds in OpenSfM

#11

Post by yubin »

deckar01 wrote: post #8

I discovered VisualSfM this weekend after trying Adobe ReCap 360. The photo reconstruction functionality of ReCap is cloud based, which was a blocker for me, because I have a beefy graphics rig and want to script it into a pipeline. I am curious how OpenSfM compares to VisualSfM and if they are related in any way. Edit: The VisualSfM license is only open for non-commercial uses. OpenSfM is BSD licensed, so I can safe…

Both VisualSfM and OpenSfM use similar methodology (incremental structure from motion) to reconstruct 3D scene points and camera positions from photos.

And yes, you can build your own tools (even commercially) with OpenSfM.

Re: Denser 3D Point Clouds in OpenSfM

#13

Post by yorwba »

deckar01 wrote: post #8

I discovered VisualSfM this weekend after trying Adobe ReCap 360. The photo reconstruction functionality of ReCap is cloud based, which was a blocker for me, because I have a beefy graphics rig and want to script it into a pipeline. I am curious how OpenSfM compares to VisualSfM and if they are related in any way. Edit: The VisualSfM license is only open for non-commercial uses. OpenSfM is BSD licensed, so I can safe…

I am curious, did you try to build VisualSfM yourself? I had to use it for a project at Uni a few years ago and the build process was quite adventurous, without this[0] guide I would have been completely lost. Would be interesting to know whether it has gotten any easier.

[0] http://www.10flow.com/2012/08/15/building-visualsfm-on-ubunt...

Re: Denser 3D Point Clouds in OpenSfM

#15

Post by dharma1 »

yubin wrote: post #10
dharma1 wrote: post #7

very cool. that's quite dense. So the segmentation convnet is applied on the 2d image pixels before SfM, rather than on the point cloud data? I've been looking for neural net semantic segmentation for 3D point cloud data

Exactly, the convnet is applied on 2d pixels instead of on 3D point clouds. If one have labelled 3D points (e.g. if a point is part of a car or not), one can train a network for recognition directly on 3D points.

Nice. I wonder if this could be used for robot navigation. The segmented point clouds especially are useful.

Been looking forward to a DIY Roomba project using point clouds and neural nets for navigation

Re: Denser 3D Point Clouds in OpenSfM

#16

Post by maxerickson »

MichailP wrote: post #14

Is it possible to use images from say Google Street View to reconstruct 3D city model with this tool? Maybe it could fall into fair use for small part of city...

It would likely violate their TOS.

No creation or augmentation of data sets based on Google’s Content or Services. You will not use Google’s Content or Services to create or augment your own mapping-related dataset (or that of a third party), including a mapping or navigation dataset, business listings database, mailing list, or telemarketing list.

There's probably some other issues.

https://developers.google.com/maps/terms

Re: Denser 3D Point Clouds in OpenSfM

#17

Post by rasmi »

MichailP wrote: post #14

Is it possible to use images from say Google Street View to reconstruct 3D city model with this tool? Maybe it could fall into fair use for small part of city...

You would need a significant number of images for a particular scene (more than Google Street View would provide -- maybe in the tens or hundreds depending on the complexity -- but perhaps mining Google Maps photo uploads for a particular location would suffice). A Google Image search for a particular landmark is likely to yield better results ([1], [2], [3]). Also, stitching together multiple scenes after reconstructing each individual scene may prove difficult. Apple Maps does a sort of satellite view projection on to 3D building models ([4]), but this is far from a dense reconstruction.

[1]http://grail.cs.washington.edu/projects/timelapse/

[2]http://grail.cs.washington.edu/projects/timelapse3d/

[3]https://grail.cs.washington.edu/rome/

[4]http://www.theverge.com/2015/9/29/9413583/apple-maps-3d-flyo...

Re: Denser 3D Point Clouds in OpenSfM

#18

Post by deckar01 »

yorwba wrote: post #13
deckar01 wrote: post #8

I discovered VisualSfM this weekend after trying Adobe ReCap 360. The photo reconstruction functionality of ReCap is cloud based, which was a blocker for me, because I have a beefy graphics rig and want to script it into a pipeline. I am curious how OpenSfM compares to VisualSfM and if they are related in any way. Edit: The VisualSfM license is only open for non-commercial uses. OpenSfM is BSD licensed, so I can safe…

I am curious, did you try to build VisualSfM yourself? I had to use it for a project at Uni a few years ago and the build process was quite adventurous, without this[0] guide I would have been completely lost. Would be interesting to know whether it has gotten any easier. [0] http://www.10flow.com/2012/08/15/building-visualsfm-on-ubunt...

No, I used the windows binaries during evaluation.

Re: Denser 3D Point Clouds in OpenSfM

#19

Post by deckar01 »

yubin wrote: post #11
deckar01 wrote: post #8

I discovered VisualSfM this weekend after trying Adobe ReCap 360. The photo reconstruction functionality of ReCap is cloud based, which was a blocker for me, because I have a beefy graphics rig and want to script it into a pipeline. I am curious how OpenSfM compares to VisualSfM and if they are related in any way. Edit: The VisualSfM license is only open for non-commercial uses. OpenSfM is BSD licensed, so I can safe…

Both VisualSfM and OpenSfM use similar methodology (incremental structure from motion) to reconstruct 3D scene points and camera positions from photos. And yes, you can build your own tools (even commercially) with OpenSfM.

I am curious how the quality compares and if they have common library dependencies.
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