点云配准方法[优质PPT]
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Construct a symmetric matrix:
仪器科学与工程学院
3. Quaternion Method
17
The unit eigenvector corresponding to the maximum
eigenvalue of matrix
:
Translation matrix:
Conclusions
仪器科学与工程学院
18
Thank you！
畅想网络 Imagination Network 感谢观看！
文章内容来源于网络，如有侵权请联系我们删除。
（d） Mensi plane target
ຫໍສະໝຸດ Baidu
仪器科学与工程学院
Figure 1 Different kinds of plane target
1. Point Cloud Registration With Target Control
5
6 spatial similarity transformation parameters 3 angle elements: 3 translation elements: Adjustment model:
Or
仪器科学与工程学院
1. Point Cloud Registration With Target Control
6
Rotation matrix:
仪器科学与工程学院
1. Point Cloud Registration With Target Control
7
The expansion of Taylor's formula: Error Equation:
仪器科学与工程学院
1. Point Cloud Registration With Target Control
4
面
（a）Leica standard rotation plane target （b） Mensi plane target
（c）FARO standard plane target
The centroid of the set of basic points :
仪器科学与工程学院
3. Quaternion Method
16
Orthogonal covariance matrix of point set: Antisymmetric matrix’s cyclic components:
11
Error equation:
仪器科学与工程学院
1. Point Cloud Registration With Target Control
12
New approximate value:
Iteration:
Finally, we get the values of parameter:
仪器科学与工程学院
ABriefIntroductionOfPointCl oudRegistrationMethod
Point Cloud Registration Method
2
1 Point Cloud Registration With Target Control 2 Iterative Closest Point(ICP) Algorithm 3 Quaternion Method 4
仪器科学与工程学院
1. Point Cloud Registration With Target Control
8
Derivative value:
G
Suppose that:
仪器科学与工程学院
1. Point Cloud Registration With Target Control
9
Error equation matrix:
2. Iterative Closest Point(ICP) Algorithm
13
Basic thought: Firstly, from a point set, a bar curve, or a surface to find the closest point that corresponds to one point, and then uses this result to find two corresponding point sets. Finally, we find out the corresponding point set and the corresponding transformation matrix.
3 Quaternion Method
14
What is Quaternion ? Unit quaternions
Rotation matrix R
仪器科学与工程学院
3. Quaternion Method
15
Definite translation vector: Complete registration station: Assume that: Minimum objective function:
Gravity-centralize:
仪器科学与工程学院
1. Point Cloud Registration With Target Control
10
N pairs of corresponding points:
Order:
仪器科学与工程学院
1. Point Cloud Registration With Target Control
仪器科学与工程学院
Outline
3
Two point cloud sets of A and B, are conformations of the same points in different coordinate systems
Rigid transformation:
Objective function:
Basic steps: Step1:Search for the nearest points Step2:Solve transformation relations Step3:Application transformation Step4:Repeated iteration
仪器科学与工程学院
仪器科学与工程学院
3. Quaternion Method
17
The unit eigenvector corresponding to the maximum
eigenvalue of matrix
:
Translation matrix:
Conclusions
仪器科学与工程学院
18
Thank you！
畅想网络 Imagination Network 感谢观看！
文章内容来源于网络，如有侵权请联系我们删除。
（d） Mensi plane target
ຫໍສະໝຸດ Baidu
仪器科学与工程学院
Figure 1 Different kinds of plane target
1. Point Cloud Registration With Target Control
5
6 spatial similarity transformation parameters 3 angle elements: 3 translation elements: Adjustment model:
Or
仪器科学与工程学院
1. Point Cloud Registration With Target Control
6
Rotation matrix:
仪器科学与工程学院
1. Point Cloud Registration With Target Control
7
The expansion of Taylor's formula: Error Equation:
仪器科学与工程学院
1. Point Cloud Registration With Target Control
4
面
（a）Leica standard rotation plane target （b） Mensi plane target
（c）FARO standard plane target
The centroid of the set of basic points :
仪器科学与工程学院
3. Quaternion Method
16
Orthogonal covariance matrix of point set: Antisymmetric matrix’s cyclic components:
11
Error equation:
仪器科学与工程学院
1. Point Cloud Registration With Target Control
12
New approximate value:
Iteration:
Finally, we get the values of parameter:
仪器科学与工程学院
ABriefIntroductionOfPointCl oudRegistrationMethod
Point Cloud Registration Method
2
1 Point Cloud Registration With Target Control 2 Iterative Closest Point(ICP) Algorithm 3 Quaternion Method 4
仪器科学与工程学院
1. Point Cloud Registration With Target Control
8
Derivative value:
G
Suppose that:
仪器科学与工程学院
1. Point Cloud Registration With Target Control
9
Error equation matrix:
2. Iterative Closest Point(ICP) Algorithm
13
Basic thought: Firstly, from a point set, a bar curve, or a surface to find the closest point that corresponds to one point, and then uses this result to find two corresponding point sets. Finally, we find out the corresponding point set and the corresponding transformation matrix.
3 Quaternion Method
14
What is Quaternion ? Unit quaternions
Rotation matrix R
仪器科学与工程学院
3. Quaternion Method
15
Definite translation vector: Complete registration station: Assume that: Minimum objective function:
Gravity-centralize:
仪器科学与工程学院
1. Point Cloud Registration With Target Control
10
N pairs of corresponding points:
Order:
仪器科学与工程学院
1. Point Cloud Registration With Target Control
仪器科学与工程学院
Outline
3
Two point cloud sets of A and B, are conformations of the same points in different coordinate systems
Rigid transformation:
Objective function:
Basic steps: Step1:Search for the nearest points Step2:Solve transformation relations Step3:Application transformation Step4:Repeated iteration
仪器科学与工程学院