How does this handle motion detection? Anyone tried it?
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?
Arecont Vision cameras are fun too. Casino mode, anyone?
"This feature ensures continuous full-motion recording at 30 frames per second (fps) to comply with gaming industry regulations. Casino Mode guarantees that the frame rate will not dip below 30 fps by forcing automatic bit rate and exposure control to maintain specific predetermined settings."
In my experience, budget USB cameras are not reliable as a long-term solution because they randomly stop working in different ways after days of use and must be power-cycled.
Instead I would suggest either a direct CSI connection or an external GigE camera.
I always wonder why author of such software will not add some screenshot or gif showing UI and how it does work? In features there is mention of web interface.
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?
"This feature ensures continuous full-motion recording at 30 frames per second (fps) to comply with gaming industry regulations. Casino Mode guarantees that the frame rate will not dip below 30 fps by forcing automatic bit rate and exposure control to maintain specific predetermined settings."
[1] https://www.retailitinsights.com/doc/arecont-vision-adds-cas...
Instead I would suggest either a direct CSI connection or an external GigE camera.