A Distributed Multi-view Object Tracking Algorithm under the Bayesian Framework

P; FENG Wei; HU Bo; YANG Cheng; LIN Qing; Yang Tao; P

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A Distributed Multi-view Object Tracking Algorithm under the Bayesian Framework

更新时间：2025-07-16

- A Distributed Multi-view Object Tracking Algorithm under the Bayesian Framework
- Acta Electronica Sinica Vol. 39, Issue 2, Pages: 315-321(2011)
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  CLC： TP301
- Published：2011
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P, FENG Wei, HU Bo, et al. A Distributed Multi-view Object Tracking Algorithm under the Bayesian Framework[J]. Acta Electronica Sinica, 2011, 39(2): 315-321.
DOI：

P, FENG Wei, HU Bo, et al. A Distributed Multi-view Object Tracking Algorithm under the Bayesian Framework[J]. Acta Electronica Sinica, 2011, 39(2): 315-321. DOI：

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.

Abstract

<SPAN lang=EN-US style="FONT-SIZE: 10.5pt; FONT-FAMILY: 'Times New Roman'; mso-ansi-language: EN-US; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA; mso-fareast-font-family: 宋体; mso-font-kerning: 1.0pt">In this paper

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. In our algorithm

the centralized computing unit is no longer needed. Image acquisition

processing and data fusion can be performed by each camera in parallel. Moreover

an adaptive observation model and an adaptive state transition model are also proposed to enable efficient data fusion and robust tracking against various occlusions. Experiments have verified the effectiveness of our algorithm.

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