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Research on target detection and tracking method applied to intelligent monitoring system

机译:应用于智能监控系统的目标检测与跟踪方法研究

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Target detection and tracking is a key technology in intelligent monitoring system. However, it is still difficult to design a robust, accurate and real-time target detection and tracking algorithm. Taking target Tracking as the research focus, this paper focuses on one of the current mainstream algorithms, namely, TLD (tracking-learning-detection) target Tracking algorithm. Based on the theory of TLD target tracking and corner detection, a new target tracking method was proposed to solve the existing problems. A classifier is built online to track and learn the target in real time, and a target contour detector is added in the system to complement the random forest detector to solve the problem of tracking failure. Experimental results show that the proposed algorithm can effectively overcome the influence of fast change or depth occlusion, and improve the tracking efficiency of moving targets.
机译:目标检测和跟踪是智能监控系统中的关键技术。 但是,仍难以设计坚固,准确和实时的目标检测和跟踪算法。 采用目标跟踪作为研究重点,本文重点介绍了当前主流算法之一,即TLD(跟踪学习检测)目标跟踪算法。 基于TLD目标跟踪和角探测的理论,提出了一种新的目标跟踪方法来解决现有问题。 分类器在线构建以实时地进行跟踪和学习目标,并在系统中添加目标轮廓检测器以补充随机林检测器来解决跟踪失败的问题。 实验结果表明,该算法可以有效地克服快速变化或深度闭塞的影响,提高移动目标的跟踪效率。

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