static tracking filtering

[nanodust]

I'm calibrating (single camera) OPT system - likely will expand to 2 cameras.

The default settings worked well out of the box. Very small tweaks (to distance and detection thresholds via rqt_reconfigure) helped get perfect tracking.

I save the tracks into a local mongoDB for later analysis and correlation with other sensors in the room.

Now, a few days later - the camera has not been moved, but I'm noticing there are spurious detections, a few per minute. I can tune them out by increasing track threshold, but they still sneak in, even after tracking performance has degraded.

I write as it occurs to me that the process I'm doing downstream in python (filtering single tracks that are in-place for more than 30 second window within a distance threshold) could easily be done as part of OPT.

for example:
That is, the tracker could have a 'blacklist' <x,y,z>
weight could be increment, even be assigned in RVIZ.
obvbious parameters are 'filterDistance' and 'filterTime'.
that way, the system could learn what is spurious, and auto-filter.
If the goal is to detect people, people tend to move.
The same point in the same place over hours/days/weeks is obviously not of interest.

Alternatively, if there is some means of filtering these (other than background_subtraction, or decreasing sensitivity or track detection time) let me know and I'll try.