Human tracking from a mobile agent: Optical flow and Kalman filter arbitration
Human tracking from a mobile agent: Optical flow and Kalman filter arbitration
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DOI：
10.1016/j.image.2011.06.005
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发表时间：
2012-01-01
影响因子：
3.5
通讯作者：
Kruse, Daniel
中科院分区：
文献类型：
--
作者：
Motai, Yuichi;Jha, Sumit Kumar;Kruse, Daniel
跟踪运动对象是运动分析和理解中最重要但最有问题的特征之一。卡尔曼滤波器（KF）通常用于估计和预测后续帧中的目标位置。在本文中，我们提出了一种新的和有效的跟踪方法，它执行良好，即使当目标在其运动过程中突然转向。该方法在KF和光流（OF）之间进行仲裁，以提高跟踪性能。我们的系统利用激光测量距离最近的障碍物和红外摄像机找到目标。最后，利用Arbitrate OFKF滤波器对相关数据进行融合，实现对目标的实时跟踪。实验结果表明，我们提出的方法是非常有效和可靠的估计和跟踪运动目标。(C)2011 Elsevier B.V.保留所有权利。
Tracking moving objects is one of the most important but problematic features of motion analysis and understanding. The Kalman filter (KF) has commonly been used for estimation and prediction of the target position in succeeding frames. In this paper, we propose a novel and efficient method of tracking, which performs well even when the target takes a sudden turn during its motion. The proposed method arbitrates between KF and Optical flow (OF) to improve the tracking performance. Our system utilizes a laser to measure the distance to the nearest obstacle and an infrared camera to find the target. The relative data is then fused with the Arbitrate OFKF filter to perform real-time tracking. Experimental results show our suggested approach is very effective and reliable for estimating and tracking moving objects. (C) 2011 Elsevier B.V. All rights reserved.