《计算机应用研究》|Application Research of Computers

基于改进的TLD目标跟踪算法

Target tracking algorithm based on improved TLD

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作者 胡欣,高佳丽
机构 长安大学 电子与控制工程学院,西安 710064
统计 摘要被查看 次,已被下载
文章编号 1001-3695(2019)05-067-1597-04
DOI 10.19734/j.issn.1001-3695.2018.05.0353
摘要 针对传统跟踪—学习—检测(tracking-learning-detecting,TLD)目标跟踪算法由于检测模块扫描大量子窗口而导致检测时间过长,并且在跟踪过程中当目标发生严重遮挡、形变时,TLD算法会出现跟踪失败的问题进行了研究,提出改进TLD目标跟踪算法。改进算法在检测模块前加入ViBe模型预估前景目标,极大地缩小了检测区域。追踪模块用SIFT特征匹配算法来代替原算法中的光流法,准确跟踪目标避免发生跟踪漂移,减少了计算的复杂度,提高了算法适应环境的能力。实验表明,改进后的TLD算法运行速度得到提升,并且当目标出现严重遮挡、光照强度剧烈变化时的跟踪精度也得到了很好的改善。
关键词 TLD算法; ViBe算法; SIFT特征匹配算法; 跟踪漂移
基金项目 国家自然科学基金青年基金资助项目(61701044)
本文URL http://www.arocmag.com/article/01-2019-05-067.html
英文标题 Target tracking algorithm based on improved TLD
作者英文名 Hu Xin, Gao Jiali
机构英文名 School of Electronics & Control Engineering,Chang'an University,Xi'an 710064,China
英文摘要 Aiming at the problems of that the detecting module scans a large number of sub windows, which results the detection time is too long, and when the target has serious occlusion and deformation during the tracking process, the traditional tracking learning detection(TLD) target tracking algorithm will fail to track, so this paper proposed the improved TLD target tracking algorithm. Before the detection module, it added the ViBe model to estimate the foreground target, which greatly reduced the detection area. The tracking module used the SIFT feature matching algorithm to replace the optical flow method in the original algorithm, accurately tracked the target to avoid the tracking drift, reduced the complexity of the calculation and improved the ability of the algorithm to adapt to the environment. The experiment results show that the improved TLD algorithm can improve the running speed, and the tracking accuracy can also be improved when the target is seriously occluded and the light intensity changes dramatically.
英文关键词 TLD algorithm; ViBe algorithm; SIFT feature matching algorithm; tracking drift
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收稿日期 2018/5/6
修回日期 2018/6/21
页码 1597-1600
中图分类号 TP391.4
文献标志码 A