Foreground Image Segmentation with FgSegNet

A tough challenge that remains to be solved robustly is foreground image segmentation (or background subtraction in a different perspective). The task may sound trivial: create a binary mask where only the pixels of a moving/important object are marked. However, this can become particularly difficult when real-world variabilities are introduced into the picture (no pun intended). One of the first few approaches to this task which was reasonably robust (in its time) is statistical by nature. Specifically, it involved the use of multiple Gaussian models to map the distributions of each color's values (i.e. If a pixel's color values did not match its Gaussian distributions in a particular frame, it could be determined that the pixel holds a foreground object.