Thursday, October 31, 2019
Brief memo for the units in least squares
-. A-priori reference variable has no unit (unitless). It is typically 1.0 or can be a different value for scaling.
-. Weight is determined by a-prior reference variable and a-prior variance of each observation. Therefore, the unit of weight is the same as the square of the observation unit.
-. A-posterior reference variance has no unit.
-. The variances of estimated unknown parameters after adjustment are the same as the square of the unknown parameters unit.
Monday, September 16, 2019
How to calculate areas of triangles and polygons
3 vertices and cross product
If 3 vertices' coordinates are given, the size of the cross product of the two vectors is same to two times of the triangle area.
삼각형의 3꼭지점 좌표를 알고 있다면, 인접한 두 벡터의 외적의 크기는 삼각형 면적의 두배와 같다.
$$ A = 0.5|(p_2-p_1)\times(p_3-p_1)| \tag{1}$$
If $\vec{N}$ is the result of the cross product of the two vectors, $\vec{p_1p_2}$ and $\vec{p_1p_3}$,
the size of $\vec{N}$ is same to the parallelogram including $\vec{p_1p_2}$ and $\vec{p_1p_3}$.
만약 $\vec{N}$이 두 벡터 $\vec{p_1p_2}$ and $\vec{p_1p_3}$의 외적이면,
$\vec{N}$의 크기는 두 벡터 두 벡터 $\vec{p_1p_2}$ and $\vec{p_1p_3}$을 포함하는 평행사변형의 면적과 같다.
Using the cross product and vertices' coordinates, we can get the area of a polygon by spliting a polygon into sub-triangles.
벡터외적과 꼭지점들의 좌표를 이용하면, 다각형을 내부의 작은 삼각형으로 분할하여 그 면적을 계산할 수 있다.
$$ A = \sum_{i=2}^{n-1} 0.5|(p_i-p_1)\times(p_{i+1}-p_1)| \tag{2}$$
We should know the limitation that any vector defiend by two vertices cannot intersect with any side of the polygon.두 개의 꼭지점으로 정의되는 어떤 벡터도 다각형의 어떤 변과도 만나면 안된다는 한계점을 알고 있어야 한다.
This page will be update for how to calculate a complex polygon's area.
Sunday, September 15, 2019
Photogrammetric Intersection
Linear Intersection for a Stereo Pair
There are two images.Object point vs. image point, in the first image:
$$ \begin{pmatrix} X \\ Y \\ Z \end{pmatrix} = \begin{pmatrix} X^0_a \\ Y^0_a \\ Z^0_a \end{pmatrix} + {\lambda_a}{R_a} \begin{pmatrix} x_a \\ y_a \\ -f_a \end{pmatrix} \tag{1} $$
Object point vs. image point, in the second image:
$$ \begin{pmatrix} X \\ Y \\ Z \end{pmatrix} = \begin{pmatrix} X^0_b \\ Y^0_b \\ Z^0_b \end{pmatrix} + {\lambda_b}{R_b} \begin{pmatrix} x_b \\ y_b \\ -f_b \end{pmatrix} \tag{2} $$
Therefore,
$$ \begin{pmatrix} X^0_b \\ Y^0_b \\ Z^0_b \end{pmatrix} - \begin{pmatrix} X^0_a \\ Y^0_a \\ Z^0_a \end{pmatrix} = {\lambda_a}{R_a} \begin{pmatrix} x_a \\ y_a \\ -f_a \end{pmatrix} - {\lambda_b}{R_b} \begin{pmatrix} x_b \\ y_b \\ -f_b \end{pmatrix} \tag{3} $$ $$ \begin{pmatrix} r_{11_a}x_a + r_{12_a}y_a - r_{13_a}f_a & - r_{11_b}x_b - r_{12_b}y_b + r_{13_b}f_b \\ r_{21_a}x_a + r_{22_a}y_a - r_{23_a}f_a & - r_{21_b}x_b - r_{22_b}y_b + r_{23_b}f_b \\ r_{31_a}x_a + r_{32_a}y_a - r_{33_a}f_a & - r_{31_b}x_b - r_{32_b}y_b + r_{33_b}f_b \end{pmatrix} = \begin{pmatrix} X^0_b - X^0_a \\ Y^0_b - Y^0_a \\ Z^0_b - Z^0_a \end{pmatrix} \tag{4} $$
where, $ \begin{pmatrix} X \ Y \ Z \end{pmatrix}^T $ are object coordinates,
$\begin{pmatrix} X^0_a \ Y^0_a \ Z^0_a \end{pmatrix}^T$, $\begin{pmatrix} X^0_b \ Y^0_b \ Z^0_b \end{pmatrix}^T$, $R_a$, and $R_b$ denote positoions and attitudes of two images. $\begin{pmatrix} x_a \ y_a \ -f_a \end{pmatrix}^T$ and $\begin{pmatrix} x_b \ y_b \ -f_b \end{pmatrix}^T$ are photo coordinates of each image. If two images are obtained by a camera, $f_a = f_b$.
In the equation (4), there are two unknowns ($\lambda_a$ and $\lambda_b$) and three linear equations. Once $\lambda_a$ and $\lambda_b$ are determined, we get two sets of object coordinates from two scale factors and can use mean values of them.
General Case: Linear Intersection for Multiple Images
$$ \left. \begin {matrix} \begin{pmatrix} X \\ Y \\ Z \end{pmatrix} - {\lambda_1}{R_1} \begin{pmatrix} x_1 \\ y_1 \\ -f_1 \end{pmatrix} = \begin{pmatrix} X^0_1 \\ Y^0_1 \\ Z^0_1 \end{pmatrix} \\ \begin{pmatrix} X \\ Y \\ Z \end{pmatrix} - {\lambda_2}{R_2} \begin{pmatrix} x_2 \\ y_2 \\ -f_2 \end{pmatrix} = \begin{pmatrix} X^0_2 \\ Y^0_2 \\ Z^0_2 \end{pmatrix} \\ \vdots \\ \begin{pmatrix} X \\ Y \\ Z \end{pmatrix} - {\lambda_n}{R_n} \begin{pmatrix} x_n \\ y_n \\ -f_n \end{pmatrix} = \begin{pmatrix} X^0_n \\ Y^0_n \\ Z^0_n \end{pmatrix} \end {matrix} \right ] \tag{5} $$Threrefore,
$$ \begin{pmatrix} 1 & 0 & 0 & -r_{11_1}x_1 - r_{12_1}y_1 + r_{13_1}f_1 & \cdots \\ 0 & 1 & 0 & -r_{21_1}x_1 - r_{22_1}y_1 + r_{23_1}f_1 & \cdots \\ 1 & 0 & 1 & -r_{31_1}x_1 - r_{32_1}y_1 + r_{33_1}f_1 & \cdots \\ 1 & 0 & 0 & 0 & -r_{11_2}x_2 - r_{12_1}y_2 + r_{13_2}f_2 & \cdots \\ 0 & 1 & 0 & 0 & -r_{21_2}x_2 - r_{22_2}y_2 + r_{23_2}f_2 & \cdots \\ 0 & 0 & 1 & 0 & -r_{31_2}x_2 - r_{32_2}y_2 + r_{33_2}f_2 & \cdots \\ \vdots \\ 1 & 0 & 0 & 0 & 0 & \cdots & -r_{11_n}x_n - r_{12_n}y_n + r_{13_n}f_n \\ 0 & 1 & 0 & 0 & 0 & \cdots & -r_{21_n}x_n - r_{22_n}y_n + r_{23_n}f_n \\ 0 & 0 & 1 & 0 & 0 & \cdots & -r_{31_n}x_n - r_{32_n}y_n + r_{33_n}f_n \end{pmatrix} \begin{pmatrix} X \\ Y \\ Z \\ \lambda_1 \\ \lambda_2 \\ \vdots \\ \lambda_n \end{pmatrix} = \begin{pmatrix} X^0_1 \\ Y^0_1 \\ Z^0_1 \\ X^0_2 \\ Y^0_2 \\ Z^0_2 \\ \lambda_2 \\ \vdots \\ X^0_n \\ Y^0_n \\ Z^0_n \end{pmatrix} \tag{6} $$
In the equation (6), there are $(3+n)$ unknowns ($\begin{pmatrix}X&Y&Z\end{pmatrix}^T$, and $3n$ equations. If there are 2 or more than 2 images, there should be redundancy.
Monday, August 26, 2019
[GoodToKnow] MathJax for Blogger
in 'head' of the blogger template editor in html mode, you can use MathJax expressions.
For a new line, use this block,
and, for an inline equation, use this line,
Friday, June 7, 2019
[LaTeX] Download from TeX Users Group
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Multi-byte Unicode char TCHAR strcat_s() _tcscaft_s() strcpy_s() _tcscpy_s() strncpy_s() _tcsncpy_s() strien() _tcsien() sprinif_s()...