background subtraction (problems)

there are several problems that must
be addressed by a good background removal algorithm to
correctly detect moving objects. A good background removal
algorithm should handle the relocation of background objects,
non-stationary background objects e.g. waving trees,
and image changes due to camera motion which is common
in outdoor applications e.g. wind load. A background removal
system should adapt to illumination changes whether
gradual changes (time of day) or sudden changes (lightswitch),
whether global or local changes such as shadows and interreflections.
A foreground object might have similar characteristics
as the background, it become difficult to distinguish
between them (camouflage). A foreground object that becomes
motionless can not be distinguished from a background
object that moves and then becomes motionless
(sleeping person). A common problem faced in the background
initialization phase is the existence of foreground
objects in the training period, which occlude the actual background,
and on the other hand often it is impossible to clear
an area to get a clear view of the background, this puts serious
limitations on system to be used in high traffic areas.
Some of these problems can be handled by very computationally
expensive methods, but in many applications, a short
processing time is required.

for a few see the following: POST1 - POST2 - POST3