first let me briefly explain the experimental setup: we have a transparent cube illuminated by led panels from 2 sides and 2 cameras are filming flying insects at a 90 degree to each other. The aim is to reconstruct the 3d flight trajectories from the video data. The amount of insects should not matter but for the initial phases anywhere from 1 to 1-2 dozen is expected. My search so far did not find anything similar described on the forum. Is there a way for Trackmate to compute what we need? My very basic approach was to track on each camera separately and then after camera calibration to triangulate the points in 3d. Besides doing this manually(too much work for big amount of insects), the stereo correspondence is not trivial to compute. For example one Track in the first camera is broken into many segments and I don’t know how to ‘assign’ them to the single big corresponding segment on the other camera(ideal results are as many tracks as insects with no fragmentation). Some additional information: Trackmate runs within Matlab. I’m open to ideas and thanks in advance.
Quick addition: I have read that the Kalman filter can be modified to work for 3d. Where exactly in the tracker code is the Kalman code declared, so I can experiment with it a little?