Abstract
In order to extract the key and useful features of the target in the UAV video image and strong marking ability, a feature extraction method for the UAV video image based on target tracking is proposed. The sparse beam method is used to adjust the splicing of UAV video images. Based on this, the pixel coordinates are obtained through the frame difference method to detect and locate the target. According to the target detection and positioning results, the video image of the target area is selected and preprocessed by the wavelet transform algorithm Target area video image, and extract the target area video image feature, through hierarchical particle filtering to achieve target tracking, to achieve the extraction of UAV video image feature. The experimental results show that: in the ORL database experiment, the average feature extraction percentage is 78.08%, and the average target tracking error is 1.16; in the COIL-20 database experiment, the average feature extraction percentage is 82.55%, and the average target tracking error is 1.20, which meets the needs of UAV video image feature extraction and target tracking.
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Zhang, X., Liu, Zj., Qu, Mf. (2021). Research on Feature Extraction Method of UAV Video Image Based on Target Tracking. In: Liu, S., Xia, L. (eds) Advanced Hybrid Information Processing. ADHIP 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 348. Springer, Cham. https://doi.org/10.1007/978-3-030-67874-6_25
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