I wouldn’t toss the idea just because there’s a related filter out there. (Well, actually there are two related filters. Simon’s Sandwich filter at
http://forum.doom9.org/showthread.php?s=&threadid=33817
also has some similarities.)
Medians are a good way to go for noise reduction — They’re usually a little inefficient, but they can be very robust. In other words, they don’t make the best possible use of the data, but the also don’t get messed up by unexpected stuff like interference. That’s because a median will mostly ignore the tails of a distribution, and just look at its center. (There are some sporting events which get judged with medianish filters — I think diving always tosses the low and high ranking before averaging the rest.) Medians will also do a good job with edge problems (i.e., when Y = black), while means will be biased.
I haven’t tried FluxSmooth yet, but the averaging you’re using when fluctuation is detected sounds like a good idea — It’ll probably avoid most of the usual median artifacts, like problems with very fast motion.
Skin detection sounds like it’s worth a try. Are you planning to look for specific colors, and avoid smoothing those too much? Just be sure not to claim that it “discriminates based on skin color” in the docs.