Laser & Optoelectronics Progress, Volume. 57, Issue 2, 21008(2020)
Target Tracking Algorithm Based on Adaptive Updating of Multilayer Convolution Features
Figures & Tables(6)
Fig. 1. Output images of target in VGG network. (a) Input; (b) conv3-4; (c) conv4-4; (d) conv5-4
Fig. 2. Distance precision and overlap success curves of 8 algorithms. (a) Distance precision curves; (b) overlap success curves
Fig. 3. Comparison of tracking results of 7 algorithms for six video sequences. (a) Football; (b) freeman3; (c) lemming; (d) shaking; (e) jogging2; (f) motorrolling
Table 1. DPs of different algorithms for different challenge factors
View tableTable 1. DPs of different algorithms for different challenge factors
Indicator Ours HCF SRDCF SiamFC DSST SAMF KCF FM 0.846 0.851 0.781 0.756 0.690 0.730 0.698 SV 0.889 0.875 0.874 0.825 0.784 0.748 0.770 IV 0.879 0.897 0.811 0.805 0.846 0.836 0.800 OCC 0.862 0.868 0.828 0.770 0.687 0.708 0.712 DEF 0.897 0.926 0.900 0.920 0.696 0.807 0.688 MB 0.855 0.878 0.838 0.735 0.749 0.799 0.713 IPR 0.885 0.853 0.850 0.811 0.770 0.821 0.756 OPR 0.880 0.865 0.869 0.844 0.770 0.815 0.753 OV 0.959 0.935 0.791 0.706 0.699 0.699 0.713 BC 0.905 0.905 0.811 0.901 0.695 0.802 0.706 LR 0.991 0.965 0.958 0.699 0.917 0.800 0.948
Table 2. Success rate accuracy values of different algorithms for different challenge factors
View tableTable 2. Success rate accuracy values of different algorithms for different challenge factors
Indicator Ours HCF SRDCF SiamFC DSST SAMF KCF FM 0.800 0.783 0.757 0.743 0.595 0.713 0.681 SV 0.833 0.779 0.799 0.791 0.605 0.668 0.618 IV 0.833 0.860 0.765 0.783 0.666 0.782 0.647 OCC 0.814 0.798 0.785 0.745 0.578 0.685 0.611 DEF 0.882 0.879 0.830 0.892 0.561 0.770 0.592 MB 0.779 0.786 0.818 0.703 0.646 0.772 0.644 IPR 0.849 0.784 0.819 0.799 0.625 0.750 0.627 OPR 0.856 0.817 0.820 0.822 0.609 0.750 0.619 OV 0.838 0.811 0.752 0.680 0.529 0.663 0.619 BC 0.861 0.873 0.723 0.866 0.567 0.750 0.603 LR 0.809 0.834 0.776 0.640 0.666 0.738 0.686
Table 3. Attributes of test videos
View tableTable 3. Attributes of test videos
Test video Frame Target size Challenge factor Football 362 39 ×50 OCC,IPR,OPR,BC Freeman3 474 12× 13 SV,IPR,OPR Lemming 1336 61 × 103 IV,SV,OCC,FM,OPR,OV Shaking 365 61 × 71 IV,SV,IPR,OPR,BC Jogging2 307 37×114 OCC, DEF, OPR MotorRolling 164 122 ×125 IV,SV,MB,FM,IPR,BC,LR
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Zeng Mengyuan, Shang Zhenhong, Liu Hui, Li Jianpeng. Target Tracking Algorithm Based on Adaptive Updating of Multilayer Convolution Features[J]. Laser & Optoelectronics Progress, 2020, 57(2): 21008
Paper Information
Category: Image Processing
Received: May. 28, 2019
Accepted: --
Published Online: Jan. 3, 2020
The Author Email: Shang Zhenhong (shangzhenhong@126.com)
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