基于通道可靠性和异常抑制的目标跟踪算法
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国强,吴天昊,徐伟,KALIUZHNYMykola
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Target tracking algorithm based on channel reliability and aberrance repression
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Qiang GUO,Tian-hao WU,Wei XU,Mykola KALIUZHNY
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| 表 2 在不同属性的OTB2015数据集上不同算法的距离精度 |
| Tab.2 Distance Precision of different algorithms on OTB2015 dataset with different attributes |
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| 算法 | DP | | IV | SV | OC | DEF | MB | FM | IPR | OPR | OV | BC | LR | | % | | 本研究 | 84.6 | 85.0 | 82.6 | 84.6 | 84.3 | 81.7 | 82.4 | 86.1 | 79.9 | 88.2 | 74.5 | | BACF | 80.3 | 76.9 | 73.0 | 76.4 | 74.5 | 79.0 | 79.2 | 78.1 | 75.6 | 80.5 | 74.1 | | STRCF | 83.7 | 84.0 | 81.0 | 84.1 | 82.6 | 80.2 | 81.1 | 85.0 | 76.6 | 87.2 | 73.7 | | DeepSRDCF | 78.6 | 81.7 | 82.2 | 77.9 | 82.3 | 81.4 | 81.8 | 83.5 | 78.1 | 84.1 | 70.8 | | SRDCF | 78.1 | 74.3 | 72.7 | 73.0 | 76.7 | 76.9 | 74.2 | 74.0 | 60.3 | 77.5 | 66.3 | | SRDCFDecon | 83.3 | 80.3 | 76.5 | 75.0 | 81.4 | 77.5 | 77.6 | 79.7 | 64.1 | 85.0 | 64.4 | | ARCF | 76.3 | 77.0 | 73.7 | 76.7 | 75.7 | 76.8 | 78.5 | 76.9 | 67.1 | 76.0 | 74.9 | | AutoTrack | 78.3 | 74.2 | 73.5 | 73.5 | 73.5 | 74.6 | 77.7 | 76.6 | 69.6 | 75.5 | 77.3 | | DRCF | 71.8 | 67.6 | 67.0 | 72.0 | 71.8 | 74.5 | 69.4 | 69.2 | 61.1 | 76.2 | 62.1 | | ECO_HC | 77.5 | 79.2 | 77.7 | 79.3 | 77.0 | 79.9 | 76.2 | 80.1 | 76.4 | 80.7 | 84.7 | | HCF | 83.0 | 79.8 | 77.6 | 79.0 | 80.4 | 81.5 | 86.4 | 81.6 | 67.7 | 84.3 | 83.1 | | HDT | 80.9 | 77.4 | 74.4 | 80.2 | 78.3 | 77.9 | 79.9 | 78.7 | 61.6 | 78.9 | 84.9 | | SiamFC | 74.1 | 73.8 | 72.6 | 69.3 | 70.5 | 74.3 | 74.2 | 75.6 | 66.9 | 69.0 | 84.7 | | FAST | 76.7 | 70.8 | 70.8 | 70.0 | 61.3 | 64.2 | 73.0 | 77.0 | 61.3 | 77.3 | 71.9 | | SITUP | 73.5 | 74.5 | 73.8 | 69.7 | 70.7 | 70.2 | 73.9 | 76.6 | 66.9 | 77.6 | 68.4 | | LCT | 74.3 | 67.8 | 67.8 | 68.5 | 67.0 | 68.1 | 78.1 | 74.6 | 59.2 | 73.4 | 53.7 | | KCF | 72.4 | 63.5 | 63.2 | 61.9 | 60.0 | 62.1 | 70.1 | 67.6 | 50.0 | 71.3 | 56.0 |
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