Fast Change Detection for Camera-based Surveillance Systems

Many parking garages and open parking spaces today are already equipped with surveillance cameras to increase the security of pedestrians or to record potentially illegal actions. An additional use case for such multi-camera surveillance systems is the automatic extraction of 3D-positions of objects and pedestrians. The safety of autonomous vehicles could benefit from this information in cases where the on-board sensors might be unable to detect potentially dangerous situations due to occlusion. Since the used cameras are installed statically, change detection is often employed as the first operation and all subsequent processing steps rely on its quality. Different scenarios impose specific challenges to the respective algorithms. In this paper we present an efficient algorithm for change detection which is tailored to the difficulties arising in an indoor surveillance scenario and demonstrate its applicability by adapting an existing pipeline and improving overall performance.