I am working on a problem where I have to find how many people are passing through a point and how many times they pass through. A good example use case for this problem would be counting how many times an person enter and exit the building.
Detecting people is somewhat easy, I have relatively high SNR images so I use machine learning (pedestrian detection) to see how many people come and go. Achieving this has been relatively easy. However identifying people throughout the day has been a more complex challenge.
I do not want to use faces since they just walk in so it is not always feasible to get clean face shots. They don't change cloths during the day so visually, I can relatively easily identify who is who when I watch the video without seeing faces.
Since I am able to pick out the pedestrians in bounding boxes nicely, I now need a way to compare them and barring light changes, perspective changes etc. identify if they are the same person or not.
Where should I start for this type of algos?