基于改进TLD的运动目标跟踪算法研究
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1.西安科技大学通信与信息工程学院 西安 710600; 2.西安科技大学理学院 西安 710600; 3.西安科技大学电气与控制工程学院 西安 710600

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TP391.41

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陕西省重点研发计划(2021GY338)、西安市科技局计划项目(21RGSF0017)资助


Moving target tracking based on improved TLD algorithm
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1.College of Communication and Information Technology, Xi′an University of Science and Technology,Xi′an 710600,China; 2.College of Science, Xi′an University of Science and Technology,Xi′an 710600,China; 3.College of Electrical and Control Engineering, Xi′an University of Science and Technology,Xi′an 710600,China

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    摘要:

    针对TLD目标跟踪算法在实际跟踪过程中会受到遮挡、旋转、运动模糊等问题的影响,提出了一种改进的TLD算法,在跟踪模块中引入改进FAST角点算法,并在检测模块中建立随机切块的数据增强方法下的正样本库,引入旋转不变LBP算法,设计了一个旋转不变性的分类器。跟踪模块的改进不仅保证了算法的准确度,还提升了算法的实时性。检测模块的改进使得TLD算法即使在运动目标部分被遮挡或发生形态改变的情况下依旧有很好的跟踪效果。对数据集OTB2013进行实验验证发现,本文算法与其他5种算法相比,不仅跟踪精确度高、运行速度快,还能有效提高运动目标被遮挡时的跟踪效果。

    Abstract:

    Aiming at the TLD target tracking algorithm is affected by the problems of occlusion, rotation and motion blur in the actual tracking process, an improved TLD algorithm is proposed, and an improved FAST corner point algorithm is introduced in the tracking module, as well as a positive sample library under the data enhancement method of randomly cut blocks in the detection module. A rotation invariant LBP algorithm is introduced to design a classifier with rotation invariance. The improvement of the tracking module not only ensures the accuracy of the algorithm, but also improves the realtime performance of the algorithm. The improvement of the detection module allows the TLD algorithm to track well even when the moving target is partially obscured or has changed its shape. Experimental verification of the data set OTB2013 reveals that the algorithm in this paper not only has high tracking accuracy and fast running speed compared with other five algorithms, but also can effectively improve the tracking effect when the moving target is obscured.

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朱代先,阮小曼,刁弘伟,刘佳,刘树林.基于改进TLD的运动目标跟踪算法研究[J].电子测量技术,2023,46(18):122-128

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  • 在线发布日期: 2024-01-10
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