Real world scale? about multicol-slam

[urbste]

Hi. I am glad that you got it to work! There are a couple of initializations to look into. I tried some but as initialization was not one of my main concerns I just did the quick and dirty solution.

I experimented with the following algorithms:

• Eigensolver of Kneip
• Stewenius
• 17 pt.

They are all included in OpenGV.
The six-point solution (https://github.com/jonathanventura/multi-camera-motion) seems quite promising. I added it to my fork of OpenGV but never got to test it (https://github.com/urbste/opengv/tree/master/include/opengv/relative_pose/modules/sixpt_ventura) However it will only compile on Ubuntu as apparently the computer generated solver file is to big for the Visual Studio compiler.

You will have to change the initialization functions and probably also the initialization matching pipeline.

[antithing]

Thank you for getting back to me yet again. Sorry for all the questions, but if you have a moment could you point me in the right direction to get started? (I am hoping it is as simple as swapping out a few functions, but I somehow doubt that is the case!) Would these initialization methods give repeatable, real world-scale translation values? Thank you again!

[jingdongZhang]

@urbste @antithing I am confused at the extrinsics of the cameras,could U tell me how to get it?

[CanCanZeng]

Hi @urbste @antithing , I'm struggling in make this project work with my insta360 panoramic camera, which provides a dual fisheye video. The code is working sometimes with rather simple dataset, but will fail in more natural scene. And I find that if I just use single camera, the code works well.
I checked the code in initialization and I suspect that the strategy now is not very accurate and cannot make the scale converge to real world scale. Actually, I think the scale of muti-camera slam will converge to the calibration scale, since the map point created by camera A will project to camera B later, then the projection operation will involve the calibration result, that is to say the 3D point in world coordinate will project to body system and then project to B camera system, the transformation between body and B camera is in real world scale, so if the map is not in real world scale, this projection will fail.
So if the scene is very large, and the baseline between cameras are rather small, the code may work, but if the baseline cannot be omitted in a small scene, the system will be very vulnerable.
I know maybe the thought above is wrong, but I just want to discuss with someone, sorry to bother you if you are not working on this topic.

[tanjunyao7]

Hi @urbste @antithing , I'm struggling in make this project work with my insta360 panoramic camera, which provides a dual fisheye video. The code is working sometimes with rather simple dataset, but will fail in more natural scene. And I find that if I just use single camera, the code works well. I checked the code in initialization and I suspect that the strategy now is not very accurate and cannot make the scale converge to real world scale. Actually, I think the scale of muti-camera slam will converge to the calibration scale, since the map point created by camera A will project to camera B later, then the projection operation will involve the calibration result, that is to say the 3D point in world coordinate will project to body system and then project to B camera system, the transformation between body and B camera is in real world scale, so if the map is not in real world scale, this projection will fail. So if the scene is very large, and the baseline between cameras are rather small, the code may work, but if the baseline cannot be omitted in a small scene, the system will be very vulnerable. I know maybe the thought above is wrong, but I just want to discuss with someone, sorry to bother you if you are not working on this topic.

hi, can you share your calibration file for insta360 dual fisheye camera? thanks

[PuYuuu]

Hi @urbste @antithing , I'm struggling in make this project work with my insta360 panoramic camera, which provides a dual fisheye video. The code is working sometimes with rather simple dataset, but will fail in more natural scene. And I find that if I just use single camera, the code works well. I checked the code in initialization and I suspect that the strategy now is not very accurate and cannot make the scale converge to real world scale. Actually, I think the scale of muti-camera slam will converge to the calibration scale, since the map point created by camera A will project to camera B later, then the projection operation will involve the calibration result, that is to say the 3D point in world coordinate will project to body system and then project to B camera system, the transformation between body and B camera is in real world scale, so if the map is not in real world scale, this projection will fail. So if the scene is very large, and the baseline between cameras are rather small, the code may work, but if the baseline cannot be omitted in a small scene, the system will be very vulnerable. I know maybe the thought above is wrong, but I just want to discuss with someone, sorry to bother you if you are not working on this topic.

hi, can you share your calibration file for insta360 dual fisheye camera? thanks

I am also curious about this. After I calibrated the the camera of insta360 according to the readme.md, it was lost after running several frames each time. I wonder if there is anything special to pay attention to during calibration or initialization. Thank you!

[urbste]

Hey. I think for a panoramic 360 camera it is difficult to assume a 'baseline' between the two sensors. Of course there is small difference between the projection centers of of both fisheye cameras, but they are as close together as possible by design so that the images can be stitched to a seemless panoramic image. For robust scale estimation in natural environments with several meters or more of scene depth you will need a baseline of multiple cm at least. (Look at stereo cameras for example). So even though you have two sensors it would probably make more sense to model them as one camera, so you would rather do monocular SLAM. As for MultiCol Slam it can work with one camara but the initialization routine is not made for that. ORBSlam has an elaborate Routine for monocular systems as initialisation is very crucial in the monocular case. Have a look at OpenVSLAM (although discontinued). They had a working mode for panoramic cameras.
Cheers