Unmanned Aerial Vehicles Identification and Tracking Based on Video Data Analysis

N. A. Obukhova, A. Motyko, A. Pozdeev
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Abstract

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.
基于视频数据分析的无人机识别与跟踪
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。
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