In recent years, it has become fairly common within the retail space to use (IP-based) surveillance cameras to track foot traffic (this can also be referred to as a “people counter”). This is a great idea, as it allows you to re-use existing hardware instead of having to install additional sensors.
There are numerous commercial solutions out there that are capable of doing this. I have however not been able to find any complete open source product that can track foot traffic (at least not bi-directional). I did find a few examples of OpenCV based projects, such as this one, but no source code.
That got me thinking; ZoneMinder is a popular open source video surveillance tool. Since I spent some time developing a Virtual Machine, I’m somewhat familiar with it. Not only does it support a large number of cameras (both V4L devices and IP cameras), it also comes with a number of trigger and alert abilities.
Using ZoneMinder, we should in theory be able to create a people counter. In a perfect world, the camera would be located in a hallway and pointed directly down from the ceiling, but it should work otherwise too.
Here’s what you would do:
- Configure your camera(s) in ZoneMinder.
- Define two zones narrow zones such that all people will pass through both zones (let’s call these “z1” and “z2”).
For instance, if a person comes into the store, they’d first pass through z1, and then z2. If they were to leave the store, the customer would pass z2 and then z1.
While I haven’t tested the next step, in theory, it would be possible to set up an alarm/filter based on this. Since these filters can execute external commands, it would be simple to make ZoneMinder call a script, which in turn triggers a ping to some database, such as Grafana, Graphite or similar.
Since I haven’t tested this last step, I don’t know if this is possible. However, if it does work, this would allow us to create a very cost effective people tracker.
I should also point out that my initial idea was to use a Raspberry Pi and attach some sort of IR sensor (over USB), but that would require additional hardware.
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