Is there any mature open source human detection and tracking system/algorithm?

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Have a look at the LatentSvmDetector. OpenCV already provides different classificators trained to detect people, cars, cats, airplanes...

I guess you have to implement the tracking yourself, but OpenCV also provides helpful functionality like e.g. Kalman filters for that.

UPDATE Here you can find latentsvm models not included in the OpenCV release version.

Another alternative is to use Haar classifier for pedestrian detection, assuming your "people" are either standing or moving, see this link that includes some discussion about it. I have tried the classifiers myself and movement + Haar-detection + Kalman tracking works relatively ok as long as:

1. there are not too many pedestrians on the scene, and they don't oclude each other,
2. the pedestrians don't look too small in the image (camera too far)
3. the background is not too cluttered with objects looking like pedestrians :)

Take a look at "Detection and Tracking of Multiple, Partially Occluded Humans by Bayesian Combination of Edgelet based Part Detectors" by Wu and Nevatia, here: http://iris.usc.edu/Outlines/papers/2007/wu-nevatia-ijcv07.pdf . This looks like the most practical, hands-on algorithm that I found. I do not know if it is ready to be used out of the box. The safest thing to do would be to take this algorithm as a goal, and make a roadmap of how you would evolve from the simplest detection and tracking algorithm towards that goal. Once you implement that simplest algorithm, take a look at the results, see where the failure modes are. Go on with your plan if it makes sense, or redo it given the new information you uncovered. I know it sounds risky, but the guys who wrote this are good, and with a bit of skill and luck you will get your algorithm soon enough.

HTH