Automatic Multiple Object Tracking System

Abstract: This paper deals with an intelligent image processing method for the video surveillance systems. We propose a technology detecting and tracking multiple moving objects, which can be applied to consumer electronics such as home and business surveillance systems consisting of an internet protocol (IP) camera and a network video recorder (NVR). A real-time surveillance system needs to detect moving objects robustly against noises and environment. So the proposed method uses the red-green-blue (RGB) colour background modelling with a sensitivity parameter to extract moving regions, the morphology to eliminate noises, and the blob-labelling to group moving objects. To track moving objects fast, the proposed method predicts the velocity and the direction of the groups formed by moving objects. Finally, the experiments show that the proposed method has the robustness against the environmental influences and the speed, which are suitable for the real- time surveillance system.

Keywords: multiple moving object tracking, IP camera, NVR, background modelling, morphology, blob-labelling, group tracking.