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Aircraft tracking using weak detectors with hidden Markov chain

机译:使用带有隐马尔可夫链的弱探测器进行飞机跟踪

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摘要

Tracking aircrafts in takeoff and landing procedures is a challenge task, since the appearance of the tacking object is uncertain due to different aircraft types and paintings, and its appearance is varying during the fast moving procedure. In this paper, an approach that uses weak cascade detectors with hidden Markov chain is proposed as a robust real-time aircraft tracker. While cascade detectors have the benefit of fast computation speed, hidden Markov chain model increases the overall performance in reliability and accuracy. Although the performance of the proposed approach can be improved in several ways, the motivation of this approach is to meet the required performance using as low computation cost as possible. It was demonstrated in real-case scenario that it was able to stay above 12 FPS detection frame rate in a 1080P video stream using a single 2.4GHz CPU thread, and successfully tracked all the aircrafts in field test.
机译:在起降过程中跟踪飞机是一项艰巨的任务,因为由于飞机类型和喷漆的不同,定位对象的外观不确定,并且在快速移动过程中其外观也会发生变化。在本文中,提出了一种使用带有隐马尔可夫链的弱级联检测器的方法作为鲁棒的实时飞机跟踪器。级联检测器具有计算速度快的优点,而隐马尔可夫链模型提高了可靠性和准确性的整体性能。尽管可以通过几种方法来改善所提出方法的性能,但是该方法的动机是使用尽可能低的计算成本来满足所需的性能。在实际案例中证明,它可以使用单个2.4GHz CPU线程在1080P视频流中保持高于12 FPS检测帧速率,并成功跟踪了所有飞机的现场测试。

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