基于视频数据分析的无人机识别与跟踪

N. A. Obukhova, A. Motyko, A. Pozdeev
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引用次数: 0

摘要

该方法在以下条件下实现了视频序列帧中无人机的自动捕获、跟踪和识别。场景有一个移动的背景,通常可以是非常详细的(复杂的背景),或者是平滑的;感兴趣的对象的大小从8×8到100×100像素;每帧从0到10个元素的移动速度;几个物体在框架内移动,包括感兴趣的物体;物体可以是人造的,也可以是自然的。在分割和跟踪阶段,所提出的方法允许对大小为5个块的感兴趣对象进行分割,随机误差小于15%,对大小为3-5%的对象进行分割。系统误差小于13%。在识别步骤中,平衡精度度量为0.83。本文的新颖之处在于,首次描述了一种综合的无人机检测、跟踪和识别程序的设计方法和研究成果,该程序适用于各种监视条件,并且在跟踪过程中帧内物体的大小发生重大变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Unmanned Aerial Vehicles Identification and Tracking Based on Video Data Analysis
The proposed method implements automatic capture, tracking and identification of unmanned aerial vehicles (UAVs) in video sequence frames under the following conditions. The scene has a moving background, which in general can be highly detailed (complex background), or smooth; the size of objects of interest from 8×8 to 100×100 pixels; speed of movement from zero to 10 elements per frame; several objects move within the frame, including the object of interest; objects can be both artificial and natural. The proposed method at the stage of segmentation and tracking allows to implement segmentation for objects of interest with a size up to 5 blocks with a random error less than 15% and for objects of larger sizes 3-5%. Systematic error less than 13%. At the identification step, the balanced accuracy metric is 0.83. The novelty of the presented work is that for the first time the design approach and research results of a comprehensive UAV detection, tracking and identification procedure for various surveillance conditions and with a significant change in the size of the object in the frame during tracking are described.
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