A fast and robust algorithm of motion detection for distributed outdoor surveillance

Abstract

Real-time segmentation of moving objects in video sequences is a fundamental step for surveillance systems. One of successful methods for complex background is to use a multi-color background model per pixel, like Gaussian mixture models(GMM). However, the common problem for this approach is that it suffers from high computation complexity and is unfeasible in the distributed real-time surveillance system. Furthermore, the GMM method generally can not solve the problems such as ghost, shadow and the situation of illumination changes. This paper proposed an effective scheme based on edge-characteristic and inter-frame difference. Experimental results show that the proposed algorithm can get exact moving object from complex background accurately like GMM, meanwhile dramatically reduce the operating time, which is 30% of the GMM. Furthermore, the approach can effectively eliminate the distributions of background and the changes of illumination.