Question About Fast9 Score
v is the brightness of center pixel, v_i is the i-th pixel brightness on circle. OpenCV use this code to calculate Fast9 Score.
\begin{align*}
& D = \{v - v_i\}_{i\in[0,24]}\\
&\text{for i=0 : 15} \\
&\{
\\
& \quad\quad d_{min} = \min(D_{i+1}, D_{i+2},...,D_{i+8})\\
& \quad\quad d_{max} = \max(D_{i+1}, D_{i+2},...,D_{i+8})\\
& \quad\quad q_{min}= \max(q_{min}, \min(d_{min}, D_i) )\\
& \quad\quad q_{min} = \max(q_{min}, \min(d_{min}, D_{i+9}) )\\
& \quad\quad q_{max}= \min(q_{max}, \max(d_{max}, D_i)) \\
& \quad\quad q_{max}= \min(q_{max}, \max(d_{max}, D_{i+9}))
\\
&\}
\\
&\text{score} = \max(q_{min}, -q_{max}) - 1
\end{align*}
However, in the paper: Machine learning for high-speed corner detection, the Score is:
V = \max(\sum_{x\in S_{bright}}|I_{p->x}-I_p|-t,\sum_{x\in S_{dark}}|I_p-I_{p->x}|-t )
1、Why not use the method of paper?
2、Which paper is the source of OpenCV’s method? OpenCV’s method is better?