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基于修正的背景加权直方图均值漂移和卡尔曼滤波的对象跟踪

Object Tracking Based on Corrected Background-Weighted Histogram Mean Shift and Kalman Filter
作者:Yu YangYongxing JiaChuanzhen RongYing ZhuYuan WangZheniun YueZhenxing Gao 加工时间:2014-07-28 信息来源:科技报告(Other) 索取原文[6 页]
关键词:目标跟踪;均值漂移;背景资料;卡尔曼滤波器;通信
摘 要:The classical mean shift (MS) algorithm is the best color-based method for object tracking.However,in the real environment it presents some limitations,especially under the presence of noise,objects with partial and full occlusions in complex environments.In order to deal with these problems,this paper proposes a reliable object tracking algorithm using corrected background-weighted histogram (CBWH) and the Kalman filter (KF) based on the MS method.The experimental results show that the proposed method is superior to the traditional MS tracking in the following aspects:1) it provides consistent object tracking throughout the video; 2) it is not influenced by the objects with partial and full occlusions; 3) it is less prone to the background clutter.
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