计算机工程与应用2011，Vol.47Issue(8)：204-206,3.DOI:10.3778/j.issn.1002-8331.2011.08.060
改进的基于高斯混合模型的运动目标检测算法
Improved moving objects detection algorithm based on Gaussian mixture model
摘要
Abstract
In a video surveillance system with static cameras,the moving objects'presence during the initialization to the traditional moving objects detection algorithm based on Gaussian mixture model often results in the low convergence speed. To increase the model convergence speed, an improved detection algorithm is presented. The improved method uses on-line K-means clustering algorithm to initialize the model. It also saves the memory space with the improvement to the matching rule and new Gaussian distribution generation rule during the model update. The experimental results demonstrate the improved algorithm can fast and efficiently detect moving objects,and has better robustness than the traditional algorithm.关键词
混合高斯模型/运动目标检测/在线K-均值聚类Key words
Gaussian mixture model/ moving object detection/ on-line K-means clustering分类
信息技术与安全科学引用本文复制引用
李明,赵勋杰..改进的基于高斯混合模型的运动目标检测算法[J].计算机工程与应用,2011,47(8):204-206,3.基金项目
国家自然科学基金(the National Natural Science Foundation of China under Grant No.60678051). （the National Natural Science Foundation of China under Grant No.60678051）
