I first read [Alan's answer about video noise removal][1] which lead me to this question. I found later [some algorithms ideas][2] which capture motion in a similar way (frame comparison, as Alan described).

And then I found this ["motion detection: fast and robust algorithms" paper][3] where they propose a hierarchical and conditional motion detection algorithm... I didn't read it throughly, but they seem to have isolated well all the objects in motion, since noise was almost completely removed (last image of the paper). However they say:

> As its complexity remains low, this algorithm is well suited for very
> light embedded systems. Future work will consider other difficult
> sequences with the presence of clutter like snow, rain or moving
> trees.

What if my intention was actually use their "morphological post-processing" technique to remove the detection of small objects instead of "stand-alone pixels" (their size would be defined according to the frame resolution)? This paper was published in 2009 and I found [this related paper][4], also from 2009... Are there any newer updates on this or different techniques?


  [1]: http://computergraphics.stackexchange.com/a/401/157
  [2]: http://www.codeproject.com/Articles/10248/Motion-Detection-Algorithms
  [3]: http://perso.ensta-paristech.fr/~manzaner/Publis/icip09.pdf
  [4]: http://link.springer.com/article/10.1007%2Fs11554-008-0096-7