Journal of Applied Optics, Volume. 43, Issue 6, 1088(2022)

Night vision dense crowd counting based on mid-term fusion of thermal imaging features

Guoyin REN... Xiaoqi LYU* and Yuhao LI |Show fewer author(s)
Author Affiliations
  • School of Mechanical Engineering, Inner Mongolia University of Science and Technology, Baotou 014010, China
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    References(9)

    [5] [5] LIU X, YANG J, DING W, et al. Adaptive mixture regression network with local counting map for crowd counting[C]//European Conference on Computer Vision, August 23-28, 2020, Glasgow. UK: Springer, 2020: 241-257.

    [7] [7] BOOMINATHAN L, KRUTHIVENTI S S S, BABU R V. Crowdnet: a deep convolutional network for dense crowd counting[C]//Proceedings of the 24th ACM international conference on Multimedia, October 15-19, 2016, New York, NY. United States: ACM, 2016: 640-644.

    [8] [8] SAMUEL M, SAMUEL-SOMA M A, MOVEH F F. Ai driven thermal people counting for smart window facade using portable low-cost miniature thermal imaging sensors[J]. 2020, 16(5): 1566-1574.

    [11] [11] TANG Z, XU T, LI H, et al. Exploring fusion strategies for accurate rgbt visual object tracking[J]. ArXiv Preprint ArXiv: 2201.08673, 2022.

    [15] [15] LIU Lingbo, CHEN Jiaqi, WU Hefeng, et al. Cross-modal collaborative representation learning and a large-scale rgbt benchmark for crowd counting[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 16-20, 2019, Long Beach, CA. USA: IEEE, 2021: 4823-4833.

    [16] [16] LI Yuhong, ZHANG Xiaofan, CHEN Deming. Csrnet: Dilated convolutional neural networks for understanding the highly congested scenes[C]//Proceedings of the IEEE conference on computer vision and pattern recognition, June 18-22, 2018, Salt Lake City, Utah. USA: IEEE, 2018: 1091-1100.

    [17] [17] FISCHER M, VIGNES A. An imprecise bayesian approach to thermal runaway probability[C]//International Symposium on Imprecise Probability: Theories and Applications, July 6-9, 2021, University of Granada, Granada. Spain: PMLR, 2021: 150-160.

    [18] [18] LIU Lingbo, CHEN Jiaqi, WU Hefeng, et al. Cross-modal collaborative representation learning and a large-scale RGBT benchmark for crowd counting[C]//2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). June 20-25, 2021. Nashville, TN. USA: IEEE, 2021: 4823-4833.

    [19] [19] LIU Z, HE Z, WANG L, et al. Visdrone-cc2021: The vision meets drone crowd counting challenge results[C]//Proceedings of the IEEE/CVF International Conference on Computer Vision, October 11- October 17, 2021, Montreal, BC, Canada. USA: IEEE, 2021: 2830-2838.

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    Guoyin REN, Xiaoqi LYU, Yuhao LI. Night vision dense crowd counting based on mid-term fusion of thermal imaging features[J]. Journal of Applied Optics, 2022, 43(6): 1088

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    Paper Information

    Category: Research Articles

    Received: Apr. 11, 2022

    Accepted: --

    Published Online: Nov. 18, 2022

    The Author Email:

    DOI:10.5768/JAO202243.0604007

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