Review of optical flow technique for moving object detection

Abstract

Object detection in a video is a challenging task in the field of image processing. Some applications of the domain are Human Machine Interaction (HMI), Security and Surveillance, Supplemented Authenticity, Traffic Monitoring on Roads, Medicinal Imaging etc. There happens to be a number of methods available for object detection. Each of the method has some constraints on the kind of application it has been used for. This paper presents one of such method which is termed as Optical Flow technique. This technique is found to be more robust and efficient for moving object detection and the same has been shown by an experiment in the paper. Applying optical flow to an image gives flow vectors of the points corresponding to the moving objects. Next part of marking the required moving object of interest counts to the post processing. Post processing is the legitimate contribution of the paper for moving object detection problem. This here is discussed as Blob Analysis. It is tested on datasets available online, real time videos and also on videos recorded manually. The results show that the moving objects are successfully detected using optical flow technique and the required post processing.