• Journal of Infrared and Millimeter Waves
  • Vol. 41, Issue 3, 639 (2022)
Li-Ya QIU1、2、3, Wei-Lin CHEN1、2、3, Fan-Ming LI1、3、*, Shi-Jian LIU1、3, Zheng LI1、3, and Chang TAN1、2、3
Author Affiliations
  • 1Shanghai Institute of Technical Physics,Chinese Academy of Sciences,Shanghai 200083,China
  • 2University of Chinese Academy of Sciences,Beijing 100049,China
  • 3Key Laboratory of Infrared System Detection and Imaging Technology,Chinese Academy of Sciences,Shanghai 200083,China
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    DOI: 10.11972/j.issn.1001-9014.2022.03.016 Cite this Article
    Li-Ya QIU, Wei-Lin CHEN, Fan-Ming LI, Shi-Jian LIU, Zheng LI, Chang TAN. Fast moving target detection algorithm based on LBP texture feature in complex background[J]. Journal of Infrared and Millimeter Waves, 2022, 41(3): 639 Copy Citation Text show less
    References

    [1] S JAVED, A MAHMOOD, S ALMAADEED et al. Moving object detection in complex scene using spatiotemporal structured-sparse RPCA. IEEE Transactions on Image Processing, 28, 1007-1022(2019).

    [2] A Eltantawy, M S Shehata. An accelerated sequential PCP-based method for groundmoving objects detection from aerial videos. IEEE Transactions on Image Processing, 28, 5991-6006(2019).

    [3] B REZAEI, S OSTADABBAS. Moving object detection through robust matrix completion augmented with objectness. IEEE Journal of Selected Topics in Signal Processing, 12, 1313-1323(2018).

    [4] P ZHENG, H Y BAI, Z M LI et al. Design of accurate detection and tracking algorithm for moving target under jitter interference. Chinese Journal of Scientific Instrument, 40, 90-98(2019).

    [5] Cong Wang, Mingguang Liu, Fei QI. Review of dynamic target detection and recognition algorithms for intelligent video surveillance system. Electric technology, 19, 6-11(2018).

    [6] Pengpeng Liu, R Lyu Michael, King Irwin et al. Learning by Distillation: A Self-Supervised Learning Framework for Optical Flow Estimation. IEEE transactions on pattern analysis and machine intelligence(2021).

    [7] S S Sengar, S Mukhopadhyay. Moving object area detection using normalized self-adaptive optical flow. Journal for Light and Electronoptic, 127, 6258-6267(2016).

    [8] Y GUO, Z LI, Y LIU et al. Video object extraction based on spatiotemporal consistency saliency detection. IEEE Access, 6, 35171-35181(2018).

    [9] M R ABBASIFARD, H NADERI, O I ALAMDARI et al. Efficient indexing for past and current position of moving objects on road networks. IEEE Transactions on Intelligent Transportation Systems, 19, 2789-2800(2018).

    [10] J LU, Z WANG, J ZHU. Space-time multiscale based moving object detection method. Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University, 35, 98-102(2017).

    [11] Shibo Gao, Yongmei Cheng, Yongqiang Zhao et al. Journal of infrared and millimeter waves, 33, 498-506(2014).

    [12] A G PANDO, M I MURGUIA. Analysis and trends on moving object detection algorithm techniques. IEEE Latin America Transactions, 17, 1771-1783(2019).

    [13] JUN Kong, Xinyi Tang, Min Jiang et al. Kalman filter tracking based on multi-scale feature extraction. Journal of infrared and millimeter waves, 30, 446-450(2011).

    [14] J D Romero, M J Lado, A J Mendez et al. A background modeling and foreground detection algorithm using scaling coefficients defined with a color model called lightnessred-green-blue. IEEE Transactions on Image Processing, 27, 1243-1258(2018).

    [15] C R Wren, A Azarbayejani, T Darrell et al. Pfinder: real-time tracking of the human body. IEEE Transactions on Pattern Analysis and Machine Intelligence, 19, 780-785(1997).

    [16] C Stauffer, W Grimson. Adaptive Background Mixture Models for Real-Time Tracking(1999).

    [17] KA Niranjil, C Sureshkumar. Background subtraction in dynamic environment based on modified adaptive GMM with TTD for moving object detection. Journal of Electrical Engineering & Technology, 10, 372-378(2015).

    [18] Xiuwei Zhang, Yanning ZHANG, Jun Liang. Multi-source collaborative Detection of moving Target based on Foreground and background Discriminability Evaluation Factor. Journal of infrared and millimeter waves, 34, 619-629(2015).

    [19] A ELGAMMAL, D HARWOOD, L S DAVIS et al. Non-parametric model for background subtraction, 751-767(2000).

    [20] O BARNICH, VAN DROOGENBROECK M. ViBe: A Universal background subtraction algorithm for video sequences. IEEE Transactions on Image Processing, 20, 1709-1724(2011).

    [21] Y DING, L WENHUI, F JINGTAO et al. Robust moving object detection under complex background. Computer Science and Information Systems, 7, 201-210(2010).

    [22] M HEIKKILA, M PIETIKAINEN. A texturebased method for modeling the background and detecting moving objects. IEEE Transactions on Pattern Analysis and Machine Intelligence, 28, 657-662(2006).

    [23] P Kumar, A Singhal, S Mehta et al. Real-time moving object detection algorithm on high-resolution videos using GPUs. Journal of Real-Time Image Processing, 11, 93-109(2016).

    [24] Lili Dong, Tong Zhang, Dongdong Ma et al. Infrared image Classification of Sea Background based on Directional Gradient Histogram and Local Contrast Feature. Journal of infrared and millimeter waves, 39, 650-658(2020).

    [25] T W Chua, K Leman, W Yue. Fuzzy rule-based system for dynamic texture and color based background subtraction. IEEE(2012).

    [26] T Song, L I Ou, H L Cui. A Moving Object Detection Method Based on Scene Perception. Acta Electronica Sinica(2016).

    [27] A N Lai, H Yoon, G Lee. Robust background extraction scheme using histogram-wise for real-time tracking in urban traffic video, 845-850(2008).

    [28] S Liao, X Zhu, L Zhen et al. Learning Multi-scale Block Local Binary Patterns for Face Recognition(2007).

    [29] Jia-wen Wu, Shi-yong Wang. Adaptive background modeling algorithm for gray video based on statistics. Chinese Journal of Lasers, 48, 113-125(201).

    [30] W D Min, X G Guo, Q Han. An improved ViBe algorithm and its application in traffic video processing. Optics and Precision Engineering, 25, 806-811(2017).

    [31] L H Gao. Research on Moving target Tracking Algorithm(2019).

    [32] W Yi, PM Jodoin, F Porikli et al. CDnet 2014: An expanded change Detection Benchmark Dataset. Artificial Intelligence & Image Processing.

    Li-Ya QIU, Wei-Lin CHEN, Fan-Ming LI, Shi-Jian LIU, Zheng LI, Chang TAN. Fast moving target detection algorithm based on LBP texture feature in complex background[J]. Journal of Infrared and Millimeter Waves, 2022, 41(3): 639
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