摘要
本文设计了一种多模型的图像跟踪系统,并采用集中式结构来融合各种模型的跟踪结果。由于图像中噪声的存在、遮挡现象的发生以及被跟踪对象的变形会对某些跟踪算法产生影响,因此,一个比较理想的跟踪系统应该能够融合这些跟踪算法的优点,从而稳定地跟踪目标。本系统采用了两个跟踪模式,分别是基于区域的和基于特征点的跟踪方法。两种模式分别得到量测,并由相关系数判定遮挡,从而决定哪些跟踪结果送到融合中心。仿真试验表明,这种算法能有效提高跟踪精度,并具有较强的鲁棒性。
In this paper, a multi-mode image tracking system is designed, which uses the centralized structure to fuse the tracking result of every mode. Because of the noise in image, the presence of occlusion, and the deformation of tracked target, some tracking algorithms may fail. So it is the main idea in this paper to merge the advantages from all of the tracking algorithms, and then have a robust behavior. There are two tracking models applied in this system, which are the modes based on region and distinguished points. Then these tracking modes track respectively, and the occlusion may be decided by the correlation coefficient, which determines those results that will be sent to fusion center. The experiences show that this system could improve the tracking precision, and have robust behavior.
出处
《信息与控制》
CSCD
北大核心
2003年第4期380-384,共5页
Information and Control
基金
国家973计划资助项目(2001CB309403)
