5
votes
Difference between SLAM and "3D reconstruction"?
You are right about the sameness of SLAM and 3D reconstruction. At the same time I don't think the author is misclassifying.
The english is a little non-standard. The author could have better said it ...
4
votes
Why are two cameras mounted in paralle in stereo application?
Each camera needs to be defined by 6 variables (3 position, 3 orientation). This would mean that during the calibration process, a solver needs to find 12 variables. As this is done usually with an ...
3
votes
Calculate information matrix for graph slam
The information matrix is just the inverse of the covariance matrix.
I recommend you read the page I linked, or just google covariance matrix. Essentially it contains how certain you are in your ...
2
votes
Accepted
How do I set all objects in my scene to be aligned with respect to the camera in Unity 3D?
I think the function you're looking for is TransformPoint(Vector3 position). You can describe something in coordinates that are local to the camera and use the <...
2
votes
Perspective n Point - RPnP algorithm
Since you only have 4 points, you should use the P3P algorithm. 3 points give you up to 4 solutions, and you need a fourth point to decide which one is correct. So 4 is the minimum number of points ...
2
votes
How to interpret the result of image rectification?
In Stereo Vision, image rectification is used to "warp" (remap the pixels using the translation, rotation, fundamental matrices computed from camera calibration) the image to remove distortions ...
2
votes
Difference between SLAM and "3D reconstruction"?
SLAM is jointly estimating the sensor pose and a map, based on a sensor model and sometimes a model for the pose change. The map can be represented in many different ways (e.g. landmark positions, ...
2
votes
Difference between SLAM and "3D reconstruction"?
The difference is largely intent. SLAM is largely used to describe the mapping procedure used when navigating an unknown environment. This is done online so the most recent state estimates are ...
1
vote
Accepted
Pipeline for dense reconstruction using pose estimation from orb-slam and stereo camera
Small errors and outliers in camera poses will make the reconstruction unprecise, hence you need some refinement.
You have multiple options:
Fuse the point clouds with an ICP-like algorithm.
Use a ...
1
vote
What's the difference between factor graph optimization and bundle adjustment?
The simplest explanation will be:
In structure from motion, it estimates structure(xyz points), camera locations, camera intrinsic.
In graph optimization, it only estimates camera locations. In the ...
1
vote
Is two cameras equivalent to Stereo camera setup?
The challenges you are going to face is more how to mount the cameras and find the relative positions between them (also the rotation). You can find a lot of designs for mounts for the cameras, also ...
1
vote
Is two cameras equivalent to Stereo camera setup?
Yes you can use two camera the same as using single stereo camera for depth perception.
Step on calibration camera for two camera and stereo camera is same.
1
vote
3D reconstruction of a moving object from two camera video stream
If the cameras are stationary it should work to use Structure from Motion (https://github.com/mapillary/OpenSfM). Failing that the cameras are stationary you could attempt to create a factor graph in ...
1
vote
Covariance and optimization
This is the basic slam problem. You have to find out (model) how the uncertainty of the robot affects the uncertainty of the landmarks, and visa-versa. This is done using the cross-correlation terms ...
1
vote
Ceiling depth with a monocular camera
Most packages utilize stereo images to calculate distances. StereoVision is a python package that can be used to generate 3d point clouds. Also, this will require the use of odometry information.
In ...
1
vote
Ceiling depth with a monocular camera
Not sure if I understood the problem correctly, but I understood that you wish to estimate the height of the observed objects hanging from the ceiling.
You have a mono camera but you can take two ...
1
vote
Accepted
Setting up a Structured Light Stereo system
Sounds good to me but there are some missing stages.
camera to the projector extrinsic calibration
projector intrinsic calibration
-> don't need this stage if you are not interested in the accuracy ...
1
vote
Accepted
How to tringulate many projections of a point to optimal postion?
I will assume, similar to OpenCV, that each camera is a pinhole camera, so you already corrected for things like lens distortion. In this case each visible point in 3D space $(x,y,z)$ gets projected ...
1
vote
Any reference for "3D feature matching + ICP"?
I'm not sure if this is the paper where the method was first proposed, but the 1992 paper A Method for Registration of 3-D Shapes by Best and McKay (published in IEEE Transactions on Pattern Analysis ...
1
vote
Any reference for "3D feature matching + ICP"?
Have you reviewed this article?
An Explicit Loop Closing Technique for 6D SLAM
It consists of building the 3D model of environment with heuristic loop closure using ICP and reliable feature ...
1
vote
Accepted
Relative scale in SfM
The answer simply is, it does not really matter because you're using the norm. The scale is determined by the actual translation and rotation between two cameras (which in case of monocular odometry ...
1
vote
Accepted
Forward monocular stereo vision (Structure from Motion)
It turns out this can easily be done with OpenCV - just find image features (FAST etc.) in first image, track them to the second image (get a set of corresponding features between two images) and then ...
1
vote
Accuracy of 3D scanners in featureless environments
For Kinect Fusion, and mostly all other point cloud fusion algorithms, ICP is used for aligning the clouds and creating the mesh. In a feature-less scene, ICP does not work, as there is no easy way to ...
1
vote
Why are two cameras mounted in paralle in stereo application?
Making them parallel is beneficial for reducing distortion after a rectification. We usually rectify two images for a fast matching. If speed is not your concern you can skip the rectification stage.
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