Infrared and Laser Engineering, Volume. 48, Issue 6, 626003(2019)
Infrared target tracking with correlation filter based on adaptive fusion of responses
[1] [1] Wang X, Liu L, Tang Z. Infrared human tracking with improved mean shift algorithm based on multicue fusion[J]. Applied Optics, 2009, 48(21): 4201-4212.
[2] [2] Liu R, Li X, Han L, et al. Track infrared point targets based on projection coefficient templates and non-linear correlation combined with Kalman prediction[J]. Infrared Physics and Technology, 2013, 57(2): 68-75.
[3] [3] Tang Zhengyuan, Zhao Jiajia, Yang Jie, et al. Infrared target tracking algorithm based on sparse representation model[J]. Infrared and Laser Engineering, 2012, 41(5): 1389-1395. (in Chinese)
[4] [4] Gundogdu E, Ozkan H, Demir H S, et al. Comparison of infrared and visible imagery for object tracking: Toward trackers with superior IR performance[C]//Computer Vision and Pattern Recognition Workshops, IEEE, 2015:1-9.
[5] [5] Liu Q, Lu X, He Z, et al. Deep convolutional neural networks for thermal Infrared object tracking[J]. Knowledge-Based Systems, 2017, 134: 189-198.
[6] [6] Qian K, Zhou H, Rong S, et al. Infrared dim-small target tracking via singular value decomposition and improved Kernelized correlation filter[J]. Infrared Physics and Technology, 2017, 82: 18-27.
[7] [7] Zheng Wuxing, Wang Chunping, Fu Qiang, et al. Aerial infrared target tracking based on gray and saliency features fusion[J]. Laser and Infrared, 2018, 48(3): 338-342. (in Chinese)
[8] [8] Henriques J F, Rui C, Martins P, et al. High-speed tracking with kernelized correlation filters[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2014, 37(3): 583-596.
[9] [9] He Y J, Li M, Zhang J L, et al. Infrared target tracking via weighted correlation filter[J]. Infrared Physics and Technology, 2015, 73: 103-114.
[10] [10] Qi Y, Zhang S, Qin L, et al. Hedged Deep Tracking[C]//Computer Vision and Pattern Recognition. IEEE, 2016: 4303-4311.
[11] [11] Chaudhuri K, Freund Y, Hsu D. A parameter-free hedging algorithm[C]//Advances in Neural Information processing systems, 2009: 297-305.
[12] [12] Danelljan M, Bhat G, Khan F S, et al. ECO: efficient convolution operators for tracking[C]//Computer Vision and Pattern Recognition, IEEE, 2017: 6931-6939.
[13] [13] Dalal N, Triggs B. Histograms of oriented gradients for human detection[C]//Computer Vision and Pattern Recognition Workshops, IEEE, 2005: 886-893.
[14] [14] Felsberg M. Enhanced distribution field tracking using channel representations[C]//International Conference on Computer Vision Workshops, IEEE, 2013:121-128.
[15] [15] Hou X, Zhang L. Saliency detection: a spectral residual approach[C]//Computer Vision and Pattern Recognition, IEEE, 2007: 1-8.
[16] [16] Danelljan M, Hager G, Khan F S, et al. Discriminative scale space tracking[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017, 39(8): 1561-1575.
[17] [17] Wu Shidong, Bao Hua, Zhang Chenbin, et al. Particle filter tracking based on visual saliency feature[J]. Journal of University of Science and Technology of China, 2015, 45(11): 934-942. (in Chinese)
[18] [18] Felsberg M, Kristan M, Matas J, et al. The thermal infrared visual object tracking VOT-TIR2016 challenge results[C]//Computer Vision-ECCV 2016 Workshops, 2016: 824-849.
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Fang Shengnan, Gu Xiaojing, Gu Xingsheng. Infrared target tracking with correlation filter based on adaptive fusion of responses[J]. Infrared and Laser Engineering, 2019, 48(6): 626003
Category: 信息获取与辨识
Received: Jan. 25, 2019
Accepted: Feb. 13, 2019
Published Online: Jul. 29, 2019
The Author Email: Shengnan Fang (fsn506@163.com)