摘要
针对高斯混合模型背景更新中面临的光照突变和目标与背景相互转化的问题,提出一种分情况分区域的背景自适应更新算法。首先根据当前检测目标的面积大小判别是否发生光照突变情况,采取针对性更新策略,对于未发生光照突变情况再分背景区域和目标区域分别进行背景自适应更新。其中,重点讨论了目标区域的背景更新问题,提出根据目标尺寸、运动速度和匹配次数等特征参数来调整目标区域的背景更新速率。仿真结果表明,该算法在保证了目标检测完整性的同时,提高了模型对背景变化的适应能力。
In view of the background update problems based on Gaussian Mixture Model（GMM）,such as sudden illumination change,mutual transformation between target and background,a new background auto-adapted update algorithm was proposed in this paper.First,the algorithm distinguished whether the sudden change of illumination occurred according to the current tested target size,and took pertinent updating measures.If there is not sudden change of illumination,the backgrouds of backgroud region and target region were updated seperately.The update of the target region was mainly discussed,and the method that adjusted the background update rate of the target region according to the target＇s characteristic parameters,such as size,velocity of movement and match times was proposed.The simulation results show that the algorithm not only guarantees the integrity of target detection,but also improves the adaptation of model to background changes.
出处
《计算机应用》
CSCD
北大核心
2011年第7期1831-1834,共4页
journal of Computer Applications
基金
中国博士后科学基金资助项目(20100471838)
陕西省自然科学基金资助项目(2010JM8014)
关键词
高斯混合模型
背景更新
运动目标检测
Gaussian Mixture Model（GMM）
background update
moving object detection
