Distributed Particle Filtering for Multiocular Soccer-Ball Tracking
Distributed Particle Filtering for Multiocular Soccer-Ball Tracking
复制标题
用于多目足球跟踪的分布式粒子滤波
DOI：
10.1109/icassp.2007.366835
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发表时间：
2007
期刊：
影响因子：
--
通讯作者：
N. Yagi
中科院分区：
文献类型：
--
作者：
T. Misu;A. Matsui;M. Naemura;Mahito Fujii;N. Yagi
提出了一种分布式多传感器融合状态估计结构。该系统由网络化的子系统组成，这些子系统根据自己的观测结果协同估计共同目标的状态。每个子系统都配备了一个独立的粒子过滤器，可以独立运行，也可以在网络模式下运行，具有粒子交换功能。我们将这种灵活的架构应用于3D足球跟踪，通过建模与目标的质心，大小和运动模糊相关的成像过程，并通过建模与弹道运动，反弹和滚动的动态。为了评估该系统的精度和鲁棒性，我们进行了实验，使用多目图像的专业足球比赛。
This paper proposes a distributed state estimation architecture for multi-sensor fusion. The system consists of networked subsystems that cooperatively estimate the state of a common target from their own observations. Each subsystem is equipped with a self-contained particle filter that can operate in stand-alone as well as in network mode with a particle exchange function. We applied this flexible architecture to 3D soccer-ball tracking by modeling the imaging processes related to the centroid, size, and motion-blur of a target, and by modeling the dynamics with ballistic motion, bounce, and rolling. To evaluate the precision and robustness of the system, we conducted experiments using multiocular images of a professional soccer match.