Enhanced moving object detection using tracking system for video surveillance purposes

Foreground extraction and moving object detection are often used in human tracking systems. However those methods are not able to produce accurate results when objects are too close or when occlusions happen since the result is generally a single big blob which contains all the different objects. In this paper we propose a novel and efficient moving object detection enhancement method. Indeed, by using the results of the previous iteration tracking we are able to keep a correct number of moving objects by removing useless blobs and by splitting those which contain more than one tracker. The method can also speed up the tracking by creating a link between a tracker and a blob to avoid unnecessary processing in some situations.