工矿自动化2012，Vol.38Issue(2)：32-35,4.DOI:32-1627/TP.20120113.1304.010
基于改进的MeanShift算法的选煤厂人员目标跟踪方法
Personnel Tracking Method of Coal Preparation Plant Based on Improved MeanShift Algorithm
翟乃江 1李承冬2
作者信息
- 1. 上海大屯能源股份有限责任公司江苏分公司,江苏徐州 221611
- 2. 中国矿业大学信电学院,江苏徐州 221116
- 折叠
摘要
Abstract
In view of problem of object losing because that traditional MeanShift algorithm used in intelligent video monitoring is easy to be disturbed by background, the paper proposed a personnel tracking method of coal preparation plant combining with MeanShift algorithm and Kalman filtering algorithm. The method firstly segments object tracking region through motion detection method, and predicts starting point of next frame tracking window through Kalman filtering algorithm, then uses MeanShift algorithm to track object region on the basis. In order to prevent tracking failure because of complex environment of coal preparation plant, the method combines with tracking and detection to further ensure robustness of tracking. The experiment result showed that the method can eliminate influence of similar color region in background and has better tracking effect.关键词
选煤厂/智能视频监控/人员跟踪/MeanShift算法/卡尔曼滤波算法Key words
coal preparation plant/intelligent video monitoring/personnel tracking/MeanShift algorithm/Kalman filtering algorithm分类
矿业与冶金引用本文复制引用
翟乃江,李承冬..基于改进的MeanShift算法的选煤厂人员目标跟踪方法[J].工矿自动化,2012,38(2):32-35,4.
