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基于贝叶斯理论的分布式多视角目标跟踪算法 被引量：7

A Distributed Multi-View Object Tracking Algorithm Under the Bayesian Framework
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摘要 为了有效解决传统单视角跟踪难于处理的目标遮挡问题,本文提出了一种分布式多视角目标跟踪算法.该算法首先基于贝叶斯理论,为多视角目标跟踪问题建立了分布式数据融合的概率框架;并利用粒子滤波器对所需后验概率进行近似,提出了自适应的观测模型和状态转移模型.各摄像机能够并行化地进行数据采集、处理、融合,而无需集中式处理单元;能够有效避免遮挡造成的误差传递,提高跟踪算法的鲁棒性.实验证明了本文算法的有效性. A distributed multi-view object tracking algorithm is proposed to address the occlusion problem.The Bayesian sequential tracking framework is used to model the multi-view tracking problem and implemented with particle filtering.The centralized computing unit is no longer needed. Image acquisition,processing and data fusion can be performed by each camera in parallel.An adaptive observation model and an adaptive state transition model are also proposed to enable efficient data fusion and robusttracking against various occlusions. Experiments have verified the effectiveness of the algorithm.
作者 冯巍 胡波 杨成 林青 杨涛
机构地区 复旦大学电子工程系
出处 《电子学报》 EI CAS CSCD 北大核心 2011年第2期315-321,共7页 Acta Electronica Sinica
基金 国家973重点基础研究发展计划(No.2006CB705700) 国家自然科学基金(No.60972024)
关键词 分布式多视角目标跟踪 粒子滤波器 自适应观测模型 自适应状态转移模型 distributed multi-view object tracking particle filtering adaptive observation model adaptive state transition
分类号 TN911.73 [电子电信—通信与信息系统]
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参考文献16

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二级参考文献18

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共引文献30

同被引文献75

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引证文献7

二级引证文献23

电子学报
2011年 第2期

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