Is it feasible to try and classify an enclosed space as being a. Very crowded b. Less crowded & c. Sparsely crowded using image processing? The idea is to get three classifications for crowd: High, low and medium based on an image captured inside a train compartment. Something like this:


This gets classified in the 'High' category

http://www.spiceflair.com/wp-content/uploads/2012/05/14a.jpg 
This perhaps in the 'Medium' &amp; so on.
This sounds feasible (and fun!), but it will be hard to get very accurate.  My guess is that, like your tags suggest, this would be a combination of edge detection / space detection to get a measure of density and face/hand detection to get a measure of human content.  You could then train up an SVM or RandomForest model on the data, tweak, and repeat.