Title :
An Improved Mixture Gaussian Models to Detect Moving Object Under Real-Time Complex Background
Author :
Ju, Shiguang ; Chen, Xiaojun ; Xu, Guanghua
Author_Institution :
Coll. of Comput. Sci. & Commun. Eng., JiangSu Univ., Zhenjiang
Abstract :
With video inspecting applied, many research efforts have focused on subtracting the moving object. In this paper, we propose an improved Mixture Gaussian Model to subtract the real-time complex background. The experimental results have testified the proposed method can greatly extract the background model from the actual scene through the real-time monitor, extract the moving vessels automatically, filtrate the video abnormal incidents occurred, and achieve the monitoring the dock at no duty of intelligent monitoring.
Keywords :
Gaussian processes; computer vision; object detection; video surveillance; dock monitoring; intelligent monitoring; mixture Gaussian model; moving object detection; moving vessels; real-time complex background model; real-time monitor; video abnormal incidents; video inspection; Computerized monitoring; Database systems; Digital cameras; Hardware; Inspection; Layout; Local area networks; Network servers; Object detection; Rivers; Computer vision; background subtraction; mixture Gaussian model; moving object detection; video inspecting system;
Conference_Titel :
Cyberworlds, 2008 International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-0-7695-3381-0
DOI :
10.1109/CW.2008.117