• Laser & Optoelectronics Progress
  • Vol. 58, Issue 20, 2015007 (2021)
Li Na1、2, Fan Kuangang1、2、*, Liu Yahui1、2, and Ouyang Qinghua1、2
Author Affiliations
  • 1School of Electrical Engineering and Automation, Jiangxi University of Science and Technology, Ganzhou, Jiangxi 341000, China
  • 2Key Laboratory of Magnetic Levitation Technology in Jiangxi Province, Ganzhou, Jiangxi 341000, China
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    Abstract

    The popularization of unmanned aerial vehicle (UAV) has brought great security risks to people. A UAV video detection algorithm based on the active subspace robust principal component analysis (ASRPCA) fused with the five-frame difference is designed to solve this problem. First, an alternating iteration method combined with the augmented Lagrange multiplier method is used to optimize and solve the ASRPCA model, thereby obtaining the background image of the current frame of the video sequence. Second, the background image replaces the intermediate frame of the five-frame difference. Finally, differential binarization operation is performed simultaneously on the intermediate frames, previous two frames, and subsequent two frames. This makes UAV have a better detection result and a denoising ability. The experimental results show that under different backgrounds, compared with the algorithm of total variation regularized RPCA (TVRPCA), the average of recall rate, precision rate, and comprehensive performance of the proposed algorithm is increased by 5 percent, 4.8 percent, and 5 percent, respectively. The running time is approximately 0.51 s per frame, which meets the offline real-time requirements of the target algorithms.
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    Na Li, Kuangang Fan, Yahui Liu, Qinghua Ouyang. Unmanned Aerial Vehicle Detection Based on ASRPCA Fused with Five-Frame Difference[J]. Laser & Optoelectronics Progress, 2021, 58(20): 2015007
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    Category: Machine Vision
    Received: Dec. 3, 2020
    Accepted: Jan. 21, 2021
    Published Online: Oct. 14, 2021
    The Author Email: Fan Kuangang (kuangangfriend@163.com)