{"title":"Unmanned Aerial Vehicles Identification and Tracking Based on Video Data Analysis","authors":"N. A. Obukhova, A. Motyko, A. Pozdeev","doi":"10.1109/DSPA48919.2020.9213287","DOIUrl":null,"url":null,"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.","PeriodicalId":262164,"journal":{"name":"2020 22th International Conference on Digital Signal Processing and its Applications (DSPA)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 22th International Conference on Digital Signal Processing and its Applications (DSPA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DSPA48919.2020.9213287","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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.