Video monitoring of Landslide based on background subtraction with Gaussian mixture model algorithm

Landslides represent a major threat to human life, properties, and natural environments. Therefore, accurate monitoring landslide occurrence is very important tasks to reduce the damages and losses. Although a variety of monitoring methods have been developed, the problem of remote monitoring of suspected landslide areas that cannot be reached by human beings still cannot be solved. Moving object detection is an application of intelligent video surveillance. As a remote monitoring method, it has the ability to remotely identify moving objects. As a moving target detection algorithm, background subtraction can identify moving areas from video sequences in real time, and Gaussian mixture model algorithm is the most widely used. This paper explores the feasibility of using Gaussian mixture model algorithm to process monitoring video and monitor landslide in real time. Some landslide video is used for experiments and the results prove the efficiency of the proposed method.