Okay, here’s my blog post about setting up a people-counting system, written in a casual, personal style:
So, I’ve been messing around with this project to count people in different areas, specifically looking at airports and train stations. It’s been a real learning experience, let me tell you!
Getting Started: The Idea
It all started with a simple question: How can we get a better handle on how many people are in a specific place at a specific time? I mean, airports and train stations are busy. Knowing crowd sizes could help with, like, everything – staffing, security, even just making sure there are enough seats in the waiting area.
My first thought was, “Cameras! We gotta use cameras!” Seemed obvious, right?
The First Try: Oops!
I grabbed a basic webcam I had lying around and started tinkering. My initial plan was to use some simple open-source software – you know, the kind that promises to do everything with a few clicks. Yeah, well, that didn’t work out so great.
- Problem #1: The software was way too sensitive. It counted, like, a coat rack as a person.
- Problem #2: It couldn’t handle multiple people at once. If two people walked by together, it counted them as one giant, blob-like person. Hilarious, but not helpful.
- Problem #3: Lighting! Oh, the lighting. Shadows were people, bright spots were people… everything was a person!
It was a mess. Back to the drawing board.
Getting (Slightly) More Serious
Okay, so I realized I needed something a bit more robust. I started looking into dedicated people-counting sensors. I ended up playing with a few different types:
- Infrared Beams: These are like the things at the entrance of some stores. They shoot a beam across a doorway, and when someone breaks the beam, it counts them. Simple, but only works for doorways, not open spaces. I quickly ditched the idea.
- Thermal Sensors: I found that they are able to detect people’s body heat. Pretty cool, but they can get confused by, say, a really hot cup of coffee. And I imagine in a busy airport, there’s a lot of hot coffee.
- Stereo Vision Cameras: I got to know that these use two lenses to create a 3D view, which is supposed to be much better at distinguishing people from, you know, luggage. This seemed promising!
I ended up going with the stereo vision camera setup. It felt like the best balance of accuracy and, well, not being totally creepy.
Setting Up the System
I mounted the camera above the area I wanted to monitor – in my test setup, it was just a hallway, but you can imagine it being a gate area or a security line. The camera connected to a small computer (a Raspberry Pi, because, why not?) that ran the counting software.
This time, I used some slightly more sophisticated software. It still had its quirks, but it was way better than my first attempt. I spent a good chunk of time “training” it – basically, showing it what a person looks like, what a suitcase looks like, what a stroller looks like, etc.
The Results (Finally!)
After a lot of tweaking, I finally got some decent results! It wasn’t perfect, but it was accurately counting people most of the time. It could handle multiple people walking together, and it wasn’t fooled by shadows (most of the time). I began to collect the data.
I learned a lot during this little project. The biggest takeaway? People-counting is harder than it looks! But it’s also pretty fascinating. I can definitely see how this kind of technology could be super useful in places like airports and train stations, helping to make things run a little smoother. I gonna keep up with it!