feat: reduce false positives when there are multiple persons in view

[ivelin]

Is your feature request related to a problem? Please describe.
Users report that fall detection triggers false positives when there are multiple persons in view. See attached screenshots.
This is a known issue for single person PoseNet models.

Describe the solution you'd like
A sophisticated solutions would be to implement multiple person tracking in a sequence of video frames.

An interim practical improvement would be to discard frames with multiple persons. This is a reasonable approach because:

• Fall detector is critically important for situations when elderly people fall while they are alone and unattended by caregivers.
• If there are multiple people in a room, then triggering a fall alert is less helpful, because presumably these people can help each other and make emergency calls as needed.

For the interim solution we can use a multi person posenet model and simply discard frames when the model detects multiple persons in a frame. That will avoid potential false fall detections. Testing shows that multi-person posenet models take slightly more CPU time for inference than single person models (2-3 fps vs 3-4 fps on rpi4), which is a reasonable tradeoff since we only need 1fps for fall detection.

Describe alternatives you've considered
A sophisticated solutions would be to implement multiple person tracking in a sequence of video frames. Respectively track and detect falls for each individual person as they move between frames.

Additional context
Screenshots from users with false positives below.