整体特征通道识别的自适应孪生网络跟踪算法
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宋鹏,杨德东,李畅,郭畅
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An adaptive siamese network tracking algorithm based on global feature channel recognition
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Peng SONG,De-dong YANG,Chang LI,Chang GUO
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表 2 10种跟踪算法在OTB上11种属性的准确度 |
Tab.2 Accuracy of ten tracking algorithms on eleven attributes of OTB |
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算法 | 光照变化 | 面内旋转 | 低分辨率 | 遮挡 | 面外旋转 | 出视野 | 尺度变化 | 快速移动 | 背景干扰 | 运动模糊 | 形变 | CFNET | 0.706 | 0.768 | 0.760 | 0.703 | 0.741 | 0.536 | 0.727 | 0.716 | 0.734 | 0.633 | 0.696 | SiamFC | 0.741 | 0.742 | 0.847 | 0.726 | 0.756 | 0.669 | 0.738 | 0.743 | 0.690 | 0.705 | 0.693 | SiamTri | 0.752 | 0.774 | 0.897 | 0.730 | 0.763 | 0.723 | 0.752 | 0.763 | 0.715 | 0.727 | 0.683 | LMCF | 0.795 | 0.755 | 0.679 | 0.736 | 0.760 | 0.693 | 0.723 | 0.730 | 0.822 | 0.730 | 0.729 | DSiamM | 0.805 | 0.807 | 0.857 | 0.794 | 0.829 | 0.684 | 0.778 | 0.759 | 0.792 | 0.721 | 0.761 | Staple | 0.787 | 0.770 | 0.631 | 0.721 | 0.730 | 0.661 | 0.715 | 0.697 | 0.766 | 0.707 | 0.743 | ECO-HC | 0.792 | 0.783 | 0.798 | 0.806 | 0.811 | 0.737 | 0.805 | 0.792 | 0.824 | 0.780 | 0.818 | DeepSRDCF | 0.786 | 0.818 | 0.708 | 0.822 | 0.835 | 0.781 | 0.817 | 0.814 | 0.841 | 0.823 | 0.779 | SiamDW | 0.854 | 0.841 | 0.882 | 0.786 | 0.842 | 0.782 | 0.842 | 0.808 | 0.800 | 0.842 | 0.831 | 本研究算法 | 0.910 | 0.898 | 0.913 | 0.846 | 0.915 | 0.792 | 0.888 | 0.866 | 0.898 | 0.875 | 0.883 |
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