Borders and faces orientation
Discerning borders of objects and face orientation with vectors, an initial computer vision theory seemed plausible but too difficult to implement.
Orthographic projection
In orthographic projection, the correspondence of a system of points of three known objects and one unknown object creates a system of equations with a unique solution of parameters. If this solution can be applied to all points of the unknown object, the object is recognized.
This works with manufactured objects but not so well with natural objects.
“Goldilocks principle”
Don’t search for features that are too big / complex, and not too small / simple. Not too big, not too small.
Face recognition
Use an integral of different recognizable points on a face: search for a correlation of 2 eyes + 1 nose, 1 nose + 1 mouth, etc.