The camera is about 5 feet away form the subject and when I capture a frame, I need to be able to tell if the frame has a human in it or not.
I have some complicated plans on implementing it, just wondering if any of you know an existing solution that I can use.
The problem you've stumbled into is actually quite complicated, and it has it's own dedicated field : Computer Vision.
This is a fairly common thing one might do, and as you suggested, you definetly shouldn't reinvent the wheel. I'm not sure if there are any algorithms or open source projects floating around.
I think your best bet is to start to look for academic papers and Computer Science lecture notes.
Here's a paper: A Line-Scan Algorithm for Identifying the Human Body
OpenCV is a mature toolset to use to start working with computer vision. Note, though, that it is a very difficult problem, and the tools are correspondingly difficult to understand and use.
If you are not using C++, OpenCV may have been wrapped for you to access with your favorite language. I use Emgu CV with C#: http://www.emgu.com/wiki/index.php/Main_Page.
The histogram of oriented gradients is a technique used to detect humans: Wikipedia HoG
Simply put, the algorithm recognizes humans by the distribution of gradient directions in the image: A circle would have a uniform gradient direction distribution, because all directions are equally frequent along the boundary. A square has a distribution with four peaks at 0°, 90°, 180° and 270°, because that's the only directions of it's boundary. A human has a distinctive direction histogram, too, and that histogram can be recognized by classical machine learning algorithms like a support vector machine or an artificial neural network. I think OpenCV contains an implementation of the HoG algorithm.