Multiple Feature Fusion based on Covariance Matrix for Visual Tracking

Fig. 4. Qualitative comparison of eight tracking algorithms. (a) Basketball; (b) Bolt; (c) David3; (d) Football1; (e) Jumping; (f) Liquor; (g) Matrix; (h) Skiing; (i) Ironman; (j) Jogging1; (k) Lemming; (l) MotorRolling

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Fig. 5. Center position error curves. (a) Basketball; (b) Bolt; (c) David3; (d) Football1; (e) Jumping; (f) Liquor; (g) Matrix; (h) Skiing; (i) Ironman; (j) Jogging1; (k) Lemming; (l) MotorRolling

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Fig. 6. Overlap rate curves. (a) Basketball; (b) Bolt; (c) David3; (d) Football1; (e) Jumping; (f) Liquor; (g) Matrix; (h) Skiing; (i) Ironman; (j) Jogging1; (k) Lemming; (l) MotorRolling

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Fig. 7. Curves of precision and success rate. (a) Precision; (b) success rate

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Fig. 8. Comparison of tracking precision under 11 scenes

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Fig. 9. Comparison of tracking success rate under 11 scenes

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Table 1. Generative rules of rotation angle of quantum rotation gate
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Table 1. Generative rules of rotation angle of quantum rotation gate
x_i b_i f(x)≥f(b) Δθ_i s(α_iβ_i)
α_iβ_i>0 α_iβ_i<0 α_i=0 β_i=0
0 0 False 0 0 0 0 0
0 0 True 0 0 0 0 0
0 1 False 0 0 0 0 0
0 1 True 0.05π -1 +1 ±1 0
1 0 False 0.01π -1 +1 ±1 0
1 0 True 0.025π +1 -1 0 ±1
1 1 False 0.005π +1 -1 0 ±1
1 1 True 0.025π +1 -1 0 ±1

Table 2. Comparison of coverage rate of tracking results%

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Table 2. Comparison of coverage rate of tracking results%

Name	DLT	TLD	Struck	ASLA	DSST	SST	MIL	Proposed algorithm
Basketball	53.9	2.3	9.93	53.9	14.3	22.2	27.5	90.1
Bolt	4.29	1.4	1.71	1.4	100.0	1.1	1.1	91.6
David3	32.9	10.7	33.73	51.6	54.0	35.7	68.3	78.6
Football1	52.4	46.0	82.4	44.6	41.9	58.1	82.4	56.7
Jumping	16.6	90.1	95.9	17.3	4.8	13.4	62.3	81.3
Liquor	20.5	56.6	41.1	23.6	40.8	23.6	20.2	91.3
Matrix	2.0	1.0	12.0	2.0	21.0	34.0	12.0	36.0
Skiing	7.4	7.4	3.7	11.1	7.4	9.9	7.4	30.4
Ironman	10.8	3.0	4.8	13.3	10.8	14.5	7.2	13.9
Jogging1	22.5	96.4	21.8	22.5	22.5	22.2	22.2	92.8
Lemming	28.0	60.5	66.2	16.9	46.0	43.0	87.2	90.8
MotorRolling	7.3	15.9	16.5	11.0	6.7	7.3	7.3	30.5

Table 3. Comparison of average center position error of tracking resultspixel

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Table 3. Comparison of average center position error of tracking resultspixel

Name	DLT	TLD	Struck	ASLA	DSST	SST	MIL	Proposed algorithm
Basketball	12.0	-	118.3	82.6	111.6	105.9	91.9	10.8
Bolt	-	-	398.8	374.7	5.0	409.9	393.5	5.6
David3	107.4	-	106.5	87.8	88.4	104.5	29.7	15.2
Football1	10.4	-	5.5	12.2	20.5	15.7	5.6	8.9
Jumping	41.9	5.9	6.7	46.1	35.2	45.7	10.0	7.6
Liquor	153.3	-	91.0	146.7	99.3	146.7	141.9	23.2
Matrix	171.1	-	194.8	65.2	59.7	54.7	55.0	33.5
Skiing	244.5	-	251.8	266.6	220.1	269.9	267.0	89.4
Ironman	211.4	-	127.6	197.5	105.7	205.4	193.4	74.3
Jogging1	113.0	6.7	62.0	104.6	112.0	114.6	96.3	12.3
Lemming	128.9	-	37.8	178.8	81.5	23.6	12.1	11.8
MotorRolling	170.7	-	145.6	201.4	289.6	377.0	161.0	101.8

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Zefenfen Jin, Zhiqiang Hou, Wangsheng Yu, Xin Wang. Multiple Feature Fusion based on Covariance Matrix for Visual Tracking[J]. Acta Optica Sinica, 2017, 37(9): 0915005

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