Improved Long Time Tracking Algorithm by Combining BRISK and Region Estimation

Fig. 2. Layout strategy of tracking points. (a) Tracking points used by traditional TLD algorithms; (b)-(d) combination of uniform points and BRISK feature points

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Fig. 3. Diagram of regional prediction

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Fig. 4. Diagram of Markov direction prediction

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Fig. 5. Results of part test of different video sequences. (a) Truck; (b) pedestrian; (c) jumper; (d) bus; (e) motorcycle

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Table 1. Comparison of tracking success rate of different algorithms%

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Table 1. Comparison of tracking success rate of different algorithms%

Imagenumber	TLD	Ref. [10]	Struckalgorithm	Proposedalgorithm
Fig. 5(a)	96.33	98.01	87.41	100.00
Fig. 5(b)	91.17	94.48	63.85	97.01
Fig. 5(c)	91.84	94.23	100.00	91.99
Fig. 5(d)	92.50	95.29	81.36	97.65
Fig. 5(e)	92.46	95.24	84.09	100.00

Table 2. Comparison of tracking center position precision of different algorithms
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Table 2. Comparison of tracking center position precision of different algorithms
Imagenumber TLD Ref. [10] Struckalgorithm Proposedalgorithm
Fig. 5(a) 9.58 7.74 13.85 5.19
Fig. 5(b) 11.72 9.81 24.61 8.27
Fig. 5(c) 12.41 5.36 5.02 4.85
Fig. 5(d) 9.66 8.28 16.94 7.73
Fig. 5(e) 10.08 7.29 13.66 6.48

Table 3. Comparison of tracking speed of different algorithmsframe/s
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Table 3. Comparison of tracking speed of different algorithmsframe/s
Imagenumber TLD Ref. [10] Struckalgorithm Proposedalgorithm
Fig. 5(a) 14.38 15.71 6.91 21.63
Fig. 5(b) 15.97 17.09 6.67 20.29
Fig. 5(c) 17.74 19.26 7.33 22.73
Fig. 5(d) 11.56 13.05 8.25 18.41
Fig. 5(e) 14.22 16.87 7.49 20.04

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Hailin Kang, Ting Zhao, Hua Zhou, Qiao Liu, Zhengping Zhang. Improved Long Time Tracking Algorithm by Combining BRISK and Region Estimation[J]. Laser & Optoelectronics Progress, 2018, 55(6): 061503

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