findConnection
Description
Examples
Create an empty imageviewset object.
vSet = imageviewset;
Add three views to the view set.
viewId1 = 10; viewId2 = 5; viewId3 = 2; vSet = addView(vSet,viewId1); vSet = addView(vSet,viewId2); vSet = addView(vSet,viewId3);
Add a connection between viewId1 and viewId2.
relPose1 = rigidtform3d(eye(3),[0 0 1]); vSet = addConnection(vSet,viewId1,viewId2,relPose1);
Add a connection between viewId2 and viewId3.
relPose2 = rigidtform3d(eye(3),[0 0 2]); vSet = addConnection(vSet,viewId2,viewId3,relPose2);
Find the connection between viewId1 and viewId2.
conn = findConnection(vSet,viewId1,viewId2)
conn=1×5 table
ViewId1 ViewId2 RelativePose InformationMatrix Matches
_______ _______ __________________ _________________ ____________
10 5 {1×1 rigidtform3d} {6×6 double} {0×2 uint32}
Check the relative pose between viewId1 and viewId2.
conn.RelativePose{:}ans =
rigidtform3d with properties:
Dimensionality: 3
Translation: [0 0 1]
R: [3×3 double]
A: [1 0 0 0
0 1 0 0
0 0 1 1
0 0 0 1]
Input Arguments
Image view set, specified as an imageviewset
object.
Initial view identifiers, specified as an M-element vector of integers. Each view identifier is unique to a specific view.
Connected view identifiers, specified as an M-element vector of integers. Each view identifier is unique to a specific view.
Output Arguments
Pairwise connections between views, returned as a four-column table. The table contains columns as described in this table. Each row corresponds to one connection.
| Column | Description |
|---|---|
ViewId1 | View identifier for the first view, specified as a unique integer. |
ViewId2 | View identifier for the second view, specified as a unique integer. |
RelativePose | Relative pose of the second view with respect to the first view, specified
as a rigidtform3d or simtform3d object. |
InformationMatrix | Information matrix, specified as a 6-by-6 matrix (when you specify
RelativePose as a rigidtform3d object) or
7-by-7 matrix (when you specify RelativePose as a
simtform3d object). The information matrix represents the
uncertainty of the measurement error and is the inverse of the covariance
matrix. |
Matches | Indices of matched feature points between two views, specified as M-by-2 matrix. |
Extended Capabilities
C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.
GPU Code Generation
Generate CUDA® code for NVIDIA® GPUs using GPU Coder™.
Version History
Introduced in R2021b
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