The setup you describe matches those in the field of computer vision if I am correct. Two cameras at 90º generates 2D frames, that are used to derive the 3D location of spots.
TrackMate does not do that out of the box. It was built for microscopy setups, where 3D images (‘stacks’) are acquired by imaging each 2D plane, and moving the focus plane through the sample. So the particle detectors built in there directly inspect the 3D image to find the 3D positions of the particles.
In your case you have to combine two sets of 2D positions to generate one set of 3D positions, then track them. TrackMate does not do that, it can only track your particles once you have the 3D positions.
I do not know where to find code that achieve such a challenge. I would start with APIs that specialise in Computer Vision (as opposed to Image Analysis for Life Sciences) such as openCV.
As for the Kalman tracker code in TrackMate, you can find it here: