  We present a complete classification of minimal problems for generic
arrangements of points and lines in space observed partially by three
calibrated perspective cameras when each line is incident to at most one point.
This is a large class of interesting minimal problems that allows missing
observations in images due to occlusions and missed detections. There is an
infinite number of such minimal problems; however, we show that they can be
reduced to 140616 equivalence classes by removing superfluous features and
relabeling the cameras. We also introduce camera-minimal problems, which are
practical for designing minimal solvers, and show how to pick a simplest
camera-minimal problem for each minimal problem. This simplification results in
74575 equivalence classes. Only 76 of these were known; the rest are new. In
order to identify problems that have potential for practical solving of image
matching and 3D reconstruction, we present several smaller natural subfamilies
of camera-minimal problems as well as compute solution counts for all
camera-minimal problems which have less than 300 solutions for generic data.
