This paper presents a practical approach for object extraction from still
images and video sequences that is both: simple to use and easy to implement.
Many image segmentation projects focus on special cases or try to use
complicated heuristics and classificators to cope with every special case. The
presented approach focuses on typical pictures and videos taken from everyday
life working under the assumption that the foreground objects are sufficiently
perceptual different from the background. The approach incorporates
experiences and user feedback from several projects that have integrated the
algorithm already. The segmentation works in realtime for video and is noise
robust and provides subpixel accuracy for still images.