### Can I use cv::fitLine() to robustly find an intersection point?

`cv::fitLine`

provide robust line fitting algorithms, that ought to be better than the regular least-square fitting.

I am wondering if `cv::fitLine`

can be "abused" to robustly find the "best" intersection point of a large number of image lines.

I can just list each image line as a 3D (homogrphic) point and then call `cv::fitLine`

.
The result after normalizing should be the best fitting point.

Is there any reason this will not work?
After all lines and point are duals in 2D space, and identical in 2D projective space.

If it does work, then what should the `param`

, `reps`

and `aeps`

parameters be?