BMVC 2004, Kingston, 7th-9th Sept, 2004

A Texture-based Method for Detecting Moving Objects
M. Heikkila, M. Pietikainen, and J. Heikkila (University of Oulu, Finland)

The detection of moving objects from video frames plays an important
and often very critical role in different kinds of machine vision applications
including human detection and tracking, traffic monitoring, humanmachine
interfaces and military applications, since it usually is one of the
first phases in a system architecture. A common way to detect moving objects
is background subtraction. In background subtraction, moving objects
are detected by comparing each video frame against an existing model of the
scene background. In this paper, we propose a novel block-based algorithm
for background subtraction. The algorithm is based on the Local Binary Pattern
(LBP) texture measure. Each image block is modelled as a group of
weighted adaptive LBP histograms. The algorithm operates in real-time under
the assumption of a stationary camera with fixed focal length. It can
adapt to inherent changes in scene background and can also handle multimodal
(pdf article)