How to Count the number of People in a room using CCTV Camera feed? I am trying to find out how can I count the number of people in a room using the feed coming in from a CCTV camera fixed in one of the top corners of the room. The number of cameras can be 2 at max but 1 for now. The objective is to only be able to tell how many persons are present in the room, in real time. The precision of it is not too important, for e.g. the system could suggest a range like "there are more than 5 people right now".

Upon browsing and researching, I came across a lot of very complex algorithms and terms related to Computer Vision and Image Processing that I have not understood at all like OpenCV, HOG, Blob Detection/Tracking, Foreground/Background Subtractions etc.

I am a design student. I do not have a background in programming. But, about a week back I got introduced to Processing. So, if some could help me out here with some tutorials/references/code to have it work in a language like Processing for prototyping purposes.

Thanks in advance.
This is clearly not an easy task.

The problem is, if you want a more-or-less accurate count, then you need to turn to advanced algorithms (and maybe use 2 cameras, or a kinect).

If you can't afford to take this path, then you need to try simpler options. Personally, I would try the following:


detecting skin pixels, segmenting the image with respect to that, then count the blobs (complexity medium);
detect faces, then count them. Obviously, people have to be facing the camera, but you can find any implementations of face detection with different libraries (complexity low);
use background subtraction (after some careful tuning to take into account natural illumination changes) and guess a count based on the number of pixels that belong to the foreground (complexity low, but expect poor results);
apply some existing pedestrian detection algorithm (complexity medium to high).


You don't have to implement all that by yourself. In your case, checking what OpenCV can do (or if your algorithm of choice is implemented in OpenCV) seems a good choice because:


Processing and openFrameworks have wrappers to OpenCV;
OpenCV usually has a good runtime performance;
many computer vision algorithms that will interest you are developed with OpenCV (face detection, background subtraction, probably pedestrian detection).