[1]彭青艳,赵勋杰,陈家波. 跟踪窗口尺寸自适应调整的粒子滤波跟踪算法[J].红外技术,2012,34(10):568-572.
 PENG Qing-yan,ZHAO Xun-jie,CHEN Jia-bo. Adaptive Window Object Tracking for Particle Filter[J].Infrared Technology,2012,34(10):568-572.
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 跟踪窗口尺寸自适应调整的粒子滤波跟踪算法
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《红外技术》[ISSN:1001-8891/CN:CN 53-1053/TN]

卷:
34卷
期数:
2012年10期
页码:
568-572
栏目:
出版日期:
2012-12-31

文章信息/Info

Title:
 Adaptive Window Object Tracking for Particle Filter
文章编号:
1001-8891(2012)10-0568-05
作者:
 彭青艳赵勋杰陈家波
苏州大学物理科学与技术学院
Author(s):
 PENG Qing-yanZHAO Xun-jieCHEN Jia-bo
School of Physical Science and Technology, Soochow University
关键词:
 目标跟踪粒子滤波Bhattacharyya系数自适应窗口粒子平均距离
Keywords:
 target trackingparticle filterBhattacharyya coefficientadaptive windowparticle average distance
分类号:
TP391.41
文献标志码:
A
摘要:
 当目标尺度发生变化时,传统的粒子滤波跟踪算法的跟踪窗口尺寸不变,在目标尺寸变化较大时容易丢失跟踪目标。针对这一问题,提出了一种跟踪窗口自适应调整的粒子滤波跟踪方法。该方法依据运动目标区域内粒子到目标中心点的平均距离与目标尺寸的关系,建立跟踪窗口尺寸的数学模型。在两种目标模型上对所建立的数学模型进行了仿真验证。实验结果表明,当目标尺度发生变化时,跟踪窗口能够很好的随目标的尺寸变化而自适应地连续调整,改进后的算法在目标尺寸变化率很大时仍能够稳定跟踪目标。
Abstract:
This paper proposes an adaptive window object tracking method based on particle filter. It figures out size-changes of moving objects during target tracking. This method firstly establishes the gray histogram statistics of the observation model, using Bhattacharyya coefficient similarity for forecasting center position of target. Then it sets up a mathematical model for adjusting object size with a target window according to the average distance changes. The average distance is the particles in the moving target window to the target center. Experimental results indicate that the algorithm of tracking window can adaptively change with size-changes of moving objects, and the target results are good.

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备注/Memo

备注/Memo:
 收稿日期:2012-6-28
作者简介:彭青艳(1987-),女,江苏滨海人,硕士研究生,研究方向为计算机视觉及应用。
基金项目:江苏省高校自然科学基金,编号:BK2009116。
更新日期/Last Update: 2013-05-09