Moving Object Detection via Color Optical Flow and Visual Objectness Measurement

Abstract

How to find the moving object in the dynamic scene is one of the core problems in computer vision. In order to accurately detect moving objects in the video surveillance scene, optical flow algorithm and visual saliency detection technology had been researched. A moving object detection algorithm via color optical flow and visual similarity measurement is proposed in this paper. Firstly, the optical flow is detected on the visual significant color channel according to the opponent color theory, and the rough position of moving object is located. Then, two objectness measurements are defined to consider whether a region is an object in the precise positioning stage. Finally, the sliding window is used to mark the boundary box of the moving object in the sequence image. Experimental results show that the proposed algorithm is better than the classical moving object detection algorithm.