摘要
针对复杂背景环境下的多目标跟踪问题,论述了主要的数据关联技术,将目标检测算法与粒子滤波相结合,利用颜色直方图作为观测模型,并利用全领域(GNN)算法进行数据关联,提出一种改进的基于粒子滤波的多目标跟踪算法,实现了视频场景中的多个目标跟踪.该算法对于目标在场景中的频繁出现和消失、相似外表、交叉运动和短暂遮挡等均有较好的处理效果.
For the multi-target tracking problems with complex background, the data association techniques are discussed. Combing the target detection algorithm with particle filter and using color histograms as observation model, the global nearest neighbor （GNN） performs data association. An improved multi-target tracking algorithm is presented based on particle filter. The proposed algorithm is robust to the problems of the appearance and disappearance of targets, the similar appearance of targets, the cross movement of targets and short-time occlusion.
出处
《控制与决策》
EI
CSCD
北大核心
2009年第2期317-320,共4页
Control and Decision
基金
国家留学基金管理委员会比利时政府互换奖学金项目(20053303)
关键词
粒子滤波
视觉跟踪
多目标跟踪
数据关联
Particle filter
Visual tracking
Multi-target tracking
Data association
