代谢模型与LK算法结合的目标跟踪研究  

STUDY ON TARGET TRACKING COMBINING METABOLIC MODEL AND LK ALGORITHM

作　　者：刘万军[1] 李金泽[1] 姜文涛[1] 孟煜[1] 杨笑[1] 

机构地区：[1]辽宁工程技术大学软件学院,辽宁葫芦岛125105

出　　处：《计算机应用与软件》2015年第10期151-154,191,共5页Computer Applications and Software

基　　金：国家自然科学基金项目(61172144)

摘　　要：针对复杂环境下遮挡和视角变化导致目标跟踪漂移问题,提出一种新的目标代谢模型,并结合LK(Lucas-Kanade)图像配准方法,通过二阶段递进的跟踪方式,实现目标复杂运动状态下的有效跟踪。二阶段分别使用代谢模型中的动态模板和准静态模板进行跟踪,实时更新动态模板的同时,周期性更新准静态模板,利用目标运动信息与模板变化信息之间的关系,实现对目标新旧特征的代谢更新。实验结果表明,该算法有效解决了模型更新带来的跟踪漂移问题,具有较好的鲁棒性和实时性。Aiming at the problem of target tracking drift caused by occlusion and visual angle change in complex environment,this paper proposes a new target metabolic model,and achieves effective target tracking in the state of complex target motion based on the combination of Lucas-Kanade （LK）image registration algorithm and through a two-stage progressive tracking means.The two-stage progressive tracking mode utilises dynamic template and quasi-static template in metabolic model for target tracking respectively.While the dynamic template is timely updated,the quasi-static template is updated periodically as well.The metabolism update of target from old characteristics to new char-acteristics is realised by the utilisation of the relationship between the target motion information and the template change information.Experi-mental results show that the proposed method effectively solves the tracking sift problem brought about the model update,and has good quali-ties in terms of robustness and real-time property.

关 键 词：代谢模型 动态特征库 静态特征库 LK 算法 目标跟踪 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]