• Acta Optica Sinica
  • Vol. 39, Issue 6, 0615004 (2019)
Wanjun Liu1, Hu Sun2、*, and Wentao Jiang1
Author Affiliations
  • 1 School of Software, Liaoning Technical University, Huludao, Liaoning 125105, China
  • 2 Graduate School, Liaoning Technical University, Huludao, Liaoning 125105, China
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    DOI: 10.3788/AOS201939.0615004 Cite this Article Set citation alerts
    Wanjun Liu, Hu Sun, Wentao Jiang. Correlation Filter Tracking Algorithm for Adaptive Feature Selection[J]. Acta Optica Sinica, 2019, 39(6): 0615004 Copy Citation Text show less
    Schematic of overall frame
    Fig. 1. Schematic of overall frame
    Schematic of adaptive selection detection tracking
    Fig. 2. Schematic of adaptive selection detection tracking
    Schematic of redetection process
    Fig. 3. Schematic of redetection process
    Trajectory of object motion
    Fig. 4. Trajectory of object motion
    Schematic of predicted area
    Fig. 5. Schematic of predicted area
    Precisions and success rates for 8 tracking algorithms on OTB50. (a) Precision comparison; (b) success rate comparison
    Fig. 6. Precisions and success rates for 8 tracking algorithms on OTB50. (a) Precision comparison; (b) success rate comparison
    Precisions and success rates of 8 tracking algorithms on OTB100. (a) Precision comparison; (b) success rate comparison
    Fig. 7. Precisions and success rates of 8 tracking algorithms on OTB100. (a) Precision comparison; (b) success rate comparison
    Tracking results of 8 tracking algorithms in partial sequences
    Fig. 8. Tracking results of 8 tracking algorithms in partial sequences
    NumberFilter weightColor weightTotal weight
    10.70.31
    20.30.71
    30.50.51
    Table 1. Multi-weight distribution of fusion features
    FrameDetection positionFeature pointRedetection positionActual position
    1(115.5,188.0)--(115.5,188.0)
    2(115.0,195.2)--(116.5,193.5)
    3(112.0,202.5)--(110.5,201.0)
    4(107.9,203.7)--(107.5,202.5)
    5(107.8,219.1)178(108.3,205.2)(109.5,207.0)
    6(102.5,212.4)198(101.3,215.7)(99.5,217.5)
    7(93.5,212.7)226(91.1,213.8)(89.5,215.5)
    8(79.1,202.8)120(68.2,194.0)(66.0,194.5)
    9(66.0,188.8)--(67.5,188.5)
    10(79.1,182.3)--(76.5,184.5)
    Table 2. Comparison of central positions of targets
    Estimated scaleFrame
    22324252627282
    1(44,27)(45,28)(46,29)(47,29)(48,30)(51,32)(53,33)
    2(45,28)(46,29)(47,29)(48,30)(49,30)(52,32)(54,34)
    3(45,28)(47,29)(48,30)(49,30)(50,31)(53,33)(55,34)
    4(46,29)(48,30)(49,30)(50,31)(51,32)(54,34)(57,35)
    5(47,29)(49,30)(50,31)(51,32)(52,32)(55,34)(58,36)
    6(48,30)(50,31)(51,32)(52,32)(53,33)(57,35)(59,36)
    7(49,30)(51,32)(52,32)(53,33)(54,34)(58,36)(60,37)
    8(50,31)(52,32)(53,33)(54,34)(55,34)(59,36)(61,38)
    9(51,32)(53,33)(54,34)(55,34)(57,35)(60,37)(62,39)
    10(52,32)(54,34)(55,34)(57,35)(58,36)(61,38)(64,39)
    11(53,33)(55,34)(57,35)(58,36)(59,36)(62,39)(65,40)
    12(54,34)(57,35)(58,36)(59,36)(60,37)(64,39)(66,41)
    13(55,34)(58,36)(59,36)(60,37)(61,38)(65,40)(68,42)
    14(57,35)(59,36)(60,37)(61,38)(62,39)(66,41)(69,43)
    15(58,36)(60,37)(61,38)(62,39)(64,39)(68,42)(70,44)
    16(59,36)(61,38)(62,39)(64,39)(65,40)(69,43)(72,44)
    17(60,37)(62,39)(64,39)(65,40)(66,41)(70,44)(73,45)
    18(32,20)(33,21)(34,21)(34,21)(35,22)(37,23)(39,24)
    19(32,20)(34,21)(34,21)(35,22)(36,22)(38,24)(40,25)
    20(33,21)(34,21)(35,22)(36,22)(37,23)(39,24)(40,25)
    21(34,21)(35,22)(36,22)(37,23)(37,23)(40,25)(41,25)
    22(34,21)(36,22)(37,23)(37,23)(38,24)(40,25)(42,26)
    23(35,22)(37,23)(37,23)(38,24)(39,24)(41,25)(43,27)
    24(36,22)(37,23)(38,24)(39,24)(40,25)(42,26)(44,27)
    25(37,23)(38,24)(39,24)(40,25)(40,25)(43,27)(45,28)
    26(37,23)(39,24)(40,25)(40,25)(41,25)(44,27)(45,28)
    27(38,24)(40,25)(40,25)(41,25)(42,26)(45,28)(46,29)
    28(39,24)(40,25)(41,25)(42,26)(43,27)(45,28)(47,29)
    29(40,25)(41,25)(42,26)(43,27)(44,27)(46,29)(48,30)
    30(40,25)(42,26)(43,27)(44,27)(45,28)(47,29)(49,30)
    31(41,25)(43,27)(44,27)(45,28)(45,28)(48,30)(50,31)
    32(42,26)(44,27)(45,28)(45,28)(46,29)(49,30)(51,32)
    33(43,27)(45,28)(45,28)(46,29)(47,29)(50,31)(52,32)
    Optimum scale(41,25)(45,28)(46,29)(47,29)(49,30)(52,32)(53,33)
    Actual scale(43,24)(48,25)(46,27)(47,27)(53,28)(55,26)(54,27)
    Table 3. Estimated scale and actual scale information
    AlgorithmfDSSTSAMFSRDCFBACFSTAPLESTRCFECOOurs
    Mean DPOTB500.6960.6530.7360.7350.6930.8310.8680.789
    OTB1000.7420.7410.7780.8010.7950.8550.8860.819
    Mean OPOTB500.6230.5580.6520.6730.6050.6840.6980.675
    OTB1000.5830.5540.6120.6430.6040.6800.6970.654
    Table 4. Average tracking performance comparison among eight tracking algorithms
    AlgorithmfDSSTSAMFSRDCFBACFSTRCFSTAPLEECOProposed
    Mean FPS /(frame·s-1)OTB5074.7819.816.4627.9218.7655.511.4371.43
    OTB10088.4422.806.4631.9221.9068.831.3872.61
    Table 5. Average tracking speed comparison among 8 tracking algorithms
    Wanjun Liu, Hu Sun, Wentao Jiang. Correlation Filter Tracking Algorithm for Adaptive Feature Selection[J]. Acta Optica Sinica, 2019, 39(6): 0615004
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