Motion Detection in Static Backgrounds

Abstract

Motion detection plays a fundamental role in any object tracking or video surveillance algorithm, to the extent that nearly all such algorithms start with motion detection. Actually, the reliability with which potential foreground objects in movement can be identified, directly impacts on the efficiency and performance level achievable by subsequent processing stages of tracking or object recognition. However, detecting regions of change in images of the same scene is not a straightforward task since it does not only depend on the features of the foreground elements, but also on the characteristics of the background such as, for instance, the presence of vacillating elements. So, in this chapter, we have focused on the motion detection problem in the basic case, i.e., when all background elements are motionless. The goal is to solve different issues referred to the use of different imaging sensors, the adaptation to different environments, different motion speed, the shape changes of the targets, or some uncontrolled dynamic factors such as, for instance, gradual/sudden illumination changes. So, first, a brief overview of previous related approaches is presented by analyzing factors which can make the system fail. Then, we propose a motion segmentation algorithm that successfully deals with all the arisen problems. Finally, performance evaluation, analysis, and discussion are carried out.