Повышение качества видеопотока от системы технического зрения беспилотного летательного аппарата
Автор: Фраленко В.П.
Журнал: Программные системы: теория и приложения @programmnye-sistemy
Рубрика: Искусственный интеллект и машинное обучение
Статья в выпуске: 2 (57) т.14, 2023 года.
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В исследовании приведены результаты работы над программно-аппаратным комплексом для повышения качества видеоданных, получаемых от беспилотных летательных аппаратов. Рассмотрены задачи деконволюции отдельных кадров (удаление смазов) и стабилизации видеопотока с использованием методов машинного обучения и искусственного интеллекта. Представлены аналитические и практические результаты, позволившие подобрать решения для обработки данных от БПЛА в режиме реального времени.
Бпла, деконволюция, стабилизация, режим реального времени, экспериментальные данные
Короткий адрес: https://sciup.org/143180580
IDR: 143180580 | УДК: 004.42:004.896 | DOI: 10.25209/2079-3316-2023-14-2-3-26
Improving quality of video stream from the unmanned aerial vehicle technical vision system
The study contains the results of work on the software and hardware complex to improve the quality of video data obtained from unmanned aerial vehicles. Including the tasks of independent video-flow images deconvolution (motion blur removal) and stabilization of the video stream using machine learning and artificial intelligence methods. Analytical and practical results are presented that allowed to choose solutions for processing data from UAVs in real time.
Список литературы Повышение качества видеопотока от системы технического зрения беспилотного летательного аппарата
- Xiaojie Chu, Liangyu Chen, Chengpeng Chen, Xin Lu. "Improving image restoration by revisiting global information aggregation", ECCV 2022: Computer Vision - ECCV 2022 (October 23-27, 2022, Tel Aviv, Israel), Lecture Notes in Computer Science, vol. 13678, Springer, Cham, 2022, pp. 330-351 .
- Zhengzhong Tu, Hossein Talebi, Han Zhang, Feng Yang, Peyman Milanfar, Alan Bovik, Yinxiao Li. "MAXIM: multi-axis MLP for image processing", 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022, 34 pp. arXivg 2201.02973 fis
- Lei Sun, Christos Sakaridis, Jingyun Liang, Qi Jiang, Kailun Yang, Peng Sun, Yaozu Ye, Kaiwei Wang, Luc Van Gool. "Event-based fusion for motion deblurring with cross-modal attention", ECCV 2022: Computer Vision -ECCV 2022 (October 23-27, 2022, Tel Aviv, Israel), Lecture Notes in Computer Science, vol. 13678, Springer, Cham, pp. 412-428; 2023, 17 pp. arXiv^ 2112.00167 is
- Dasong Li, Yi Zhang, Ka Chun Cheung, Xiaogang Wang, Hongwei Qin, Hongsheng Li. "Learning degradation representations for image deblurring", Computer Vision - ECCV 2022, ECCV 2022, Lecture Notes in Computer Science, eds. Avidan, S., Brostow, G., Cissé, M., Farinella, G.M., Hassner, T.; 2022, 18 pp. arXivJi; 2208.05244 18
- Chong Mou, Qian Wang, Jian Zhang. "Deep generalized unfolding networks for image restoration", Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022, pp. 17399-17410, 12 pp. arXiv^ 2204.13348 fis
- L. Chen, X. Chu, X. Zhang, Sun J.. "Simple baselines for image restoration", Computer Vision - ECCV 2022, ECCV 2022, Lecture Notes in Computer Science, eds. Avidan S., Brostow G., Cissé M., Farinella G.M., Hassner T., 2022; 21 pp. arXivtSj 2204.04676 18
- Fu-Jen Tsai, Yan-Tsung Peng, Yen-Yu Lin, Chung-Chi Tsai, Chia-Wen Lin. "Stripformer: strip transformer for fast image deblurring.", Computer Vision -ECCV2022, ECCV 2022, Lecture Notes in Computer Science, vol. 13679, eds. Avidan, S., Brostow, G., Cissé, M., Farinella, G.M., Hassner, T., 2022; 17 pp. arXivtEi 2204.04627 18
- Zhendong Wang, Xiaodong Cun, Jianmin Bao, Wengang Zhou, Jianzhuang Liu, Houqiang Li. "Uformer: a general U-shaped transformer for image restoration", 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022, 17 pp. arXivKJ 2106.03106 is
- Bichen Wu, Chenfeng Xu, Xiaoliang Dai, Alvin Wan, Peizhao Zhang, Zhicheng Yan, Masayoshi Tomizuka, Joseph Gonzalez, Kurt Keutzer, Peter Vajda. Visual transformers: token-based image representation and processing for computer vision, 2020, 12 pp. arXivtef 2006.03677 1 ib
- A. Thakur, Z. Papakipos, C. Clauss, C. Hollinger, I. M. Andolina, V. Boivin, enarche-ahn, freol35241, B. Lowe, M. Schoentgen, R. Bouckenooghe. "abhiTronix/vidgear: VidGear vO.2.6", 2022. .url. 21
- Yu-Lun Liu, Wei-Sheng Lai, Ming-Hsuan Yang, Yung-Yu Chuang, Jia-Bin Huang. "Hybrid neural fusion for full-frame video stabilization", Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2021, pp. 2299-2308. arXivftî 2102.06205 21
- Shuaicheng Liu, Ping Tan, Lu Yuan, Jian Sun, Bing Zeng. "MeshFlow: minimum latency online video stabilization", ECCV 2016: Computer Vision -ECCV 2016 (October 11-14, 2016, Amsterdam, The Netherlands), Lecture Notes in Computer Science, vol. 9910, 2016, pp. 800-815. url 22
- M. Grundmann, V. Kwatra, I. Essa. "Auto-directed video stabilization with robust L1 optimal camera paths", CVPR '11: Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition (20-25 June 2011, Colorado Springs, CO, USA), IEEE Computer Society, 2011, ISBN 978-1-4577-0394-2, pp. 225-232. 23
- M. Grundmann, V. Kwatra, I. Essa. "Auto-Directed Video Stabilization with Robust L1 Optimal Camera Paths", CVPR '11: Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition (20-25 June 2011, Colorado Springs, CO, USA), IEEE Computer Society, 2011, pp. 225-232.
- Yufei Xu, Jing Zhang, Stephen J. Maybank, Dacheng Tao. "DUT: learning video stabilization by simply watching unstable videos", IEEE Transactions on Image Processing, 31 (2022), pp. 4306-4320 . arXivW 2011.14574 23
- Jinsoo Choi, In So Kweon. "Deep iterative frame interpolation for full-frame video stabilization", ACM Transactions on Graphics, 39:1 (2019), id. 4, 9 pp.
- M. Wang, G. -Y. Yang, J. -K. Lin, S. -H. Zhang, A. Shamir, S. -P. Lu, S. -M. Hu. "Deep online video stabilization with multi-grid warping transformation learning", IEEE Transactions on Image Processing, 28:5 (2019), pp. 2283-2292 . arXivgf 1909.02641 23
