Abstract:
This paper proposes a novel method to segment video sequences which undergoes gradual changes
into foreground and background layers. The background layer contains all objects which have been
stationary since the beginning of the video sequence. The foreground layer contains objects which
have entered into or move within the video scene and these objects can be moving or stationary. An
improved and adaptive Mixture of Gaussian (MoG) model with a feedback mechanism algorithm has
been formulated. The MoG model will classify every pixel in the image as belonging either the
foreground or the background layer. Every object in the foreground layer will be tracked and updated
in the MoG via the feedback mechanism. This feedback avoids stationary foreground objects being
updated into the MoG and thus affecting the approximation done by the MoG. This algorithm has
been implemented into an Intelligent Transportation System (ITS) to detect vehicles on the road in an
outdoor environment. A promising result is obtained in extracting vehicles on the road.
