Wanjun Liu, Yitong Li, Wentao Jiang. Research on High-Confidence Adaptive Feature Fusion Tracking[J]. Laser & Optoelectronics Progress, 2022, 59(22): 2210003
- Laser & Optoelectronics Progress
- Vol. 59, Issue 22, 2210003 (2022)
Fig. 1. Tracking images in different states and corresponding foreground and background color probability maps. (a) Original image; (b) foreground color probability map; (c) background color probability map
Fig. 2. Logarithmic loss function graph
Fig. 3. Partial tracking framework
Fig. 4. Target and response result graph. (a) Normal tracking; (b) response map under normal tracking; (c) background clutter; (d) response map under background clutter
Fig. 5. Schematic diagram of HCAF algorithm framework
Fig. 6. Precision and success rates of occlusion attributes on OTB100 dataset
Fig. 7. Precision and success rates of background clutter attributes on OTB100 dataset
Fig. 8. Precision and success rates on OTB100 dataset
Fig. 9. Precision and success rates on LaSOT dataset
Fig. 10. Tracking results of 10 tracking algorithms in partial sequences. (a) Basketball; (b) Human3; (c) Jogging-1; (d) Soccer
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Table 1. Parameters configuration
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Table 2. Comparison results of different parameter settings
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Table 3. Speed comparison on OTB100 and LaSOT datasets
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