I have a bunch of Nest cameras and some cheaper Tapo cameras.

The "motion detection" is night and day different. The Tapo does some basic frame-diffing and it's awful. Shadows? DING DING DiNG MOTION DETECTED! gust of wind made some blades of grass move? Motion! Spider? Motion motion motion! Turn down the sensitivity a notch or two and it won't notice a human walk across the frame 2 meters away. The Tapo ones claim to be smart but twigs and leaves still trigger pet/person/motion alerts. It makes them essentially useless.

The Nest cameras are so much better and their "human" detected is usually zero-false-negatives at the cost of one or two false-positives perhaps once every 3 or 4 months, and their app is superior (tapo one frequently needs to be false-killed to load clips). Yes I am aware that the nest ones are streaming back to google 24/7.

Tldr: naive frame-diffing sucks for this sort of thing if used outside. An open source implementation that has accurate and reliable "human detection" would be amazing. Doesn't need to be "AI" - I would hope that there is some sort of computationally reasonable OpenCV way of doing person detection. Perhaps wait for frame-diffing to flag motion then feed it to a more expensive algorithm?