Reddit mentions of Machine Vision: Theory, Algorithms, Practicalities (Signal Processing and its Applications)

I'd say that the answer to your question depends on the problem. For certain problems, such as detecting faces, there are functions out there that do everything for you. For other problems, such as circle detection, combinations of existing functions will get the job done (as MakingMacaroni describes in another comment). Then for some problems, such as abandoned luggage detection in airports, you really do need to be up on the current research and have a solid grasp of the mathematics involved.

I'd say that the task you're describing is probably in the second or third category. You might try thresholding optical flow over time, as RGKaizen suggests. Depending on how much training data you have to work with, you might also try training a machine learning classifier on one or more visual features to generate profiles of "normal" and "emergency" situations. If you expect big green tanks to appear or fires to break out, blob detection with color histogram analysis might even do the trick. They key is to make the problem as easy for the computer as possible, and figure out which of the functions OpenCV gives you are best suited for your particular situation.

Best of luck! If you go forward on this project, please let us know what you come up with!

EDIT: Here are a few resources for figuring out which functions to use, what math to apply, etc.:

• http://www.amazon.com/Machine-Learning-Hackers-Drew-Conway/dp/1449303714
  
• http://www.amazon.com/Machine-Vision-Practicalities-Applications-ebook/dp/B008B5Q79O/ref=tmm_kin_title_0
  
• The O'Reilly Learning OpenCV book is a great combination of theory and application, but make sure you get the 2nd Edition, as the first edition refers to a deprecated version of the API. I recommend purchasing the digital edition from the O'Reilly website once it becomes available.