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基于特征点光流和卡尔曼滤波的运动车辆跟踪
引用本文:孙季丰,王成清.基于特征点光流和卡尔曼滤波的运动车辆跟踪[J].华南理工大学学报(自然科学版),2005,33(10):19-23.
作者姓名:孙季丰  王成清
作者单位:华南理工大学,电子与信息学院,广东,广州,510640
基金项目:广东省工业科技攻关计划资助项目(B2320821)
摘    要:提出一种基于特征点光流的运动目标跟踪方法,将卡尔曼滤波跟踪技术和多边形跟踪策略应用于智能交通系统的运动车辆实时跟踪,使跟踪变得简单和稳定,计算机仿真结果表明,采用所提出的方法,能够以较高精度实现运动目标跟踪的目标模型选择、目标特征点选取、特征点光流计算、特征点光流聚类和目标识别,且计算量小、易于实现。

关 键 词:运动目标  实时跟踪  特征点光流  卡尔曼滤波
文章编号:1000-565X(2005)10-0019-05
收稿时间:2004-12-08
修稿时间:2004年12月8日

Tracking Method for Moving Vehicles Based on Feature-Point Optical Flow and Kalman Filtration
Sun Ji-feng,Wang Cheng-qing.Tracking Method for Moving Vehicles Based on Feature-Point Optical Flow and Kalman Filtration[J].Journal of South China University of Technology(Natural Science Edition),2005,33(10):19-23.
Authors:Sun Ji-feng  Wang Cheng-qing
Institution:College of Electronic and Information Engineering, South China Univ.of Tech., Guangzhou 510640, Guangdong, China
Abstract:A tracking method for motion objects is proposed based on the feature-point optical flow, which is then applied to the real-time tracking of moving vehicles in the intelligent traffic system. In the proposed method, the Kalman filtration and the polygonal tracking strategy are adopted, thus simplifying and stabilizing the tracking. Si-mulated results indicate that the proposed method can accurately determine the maneuvering target, extract the feature points, implement the computing and clustering of the feature-point optical flow and recognize moving objects. Moreover, it is of less computation and is easy to implement.
Keywords:motion object  real-time tracking  feature-point optical flow  Kalman filtration
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