Laser & Optoelectronics Progress, Volume. 57, Issue 18, 181024(2020)

Fast Face Recognition Method Based on Sparse Representation

Wei Liu* and Hongwei Ge
Author Affiliations
  • Key Laboratory of Advanced Process Control for Light Industry, Ministry of Education,
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    Figures & Tables(10)
    • Table 1. 0 Recognition accuracy of different algorithms on FEI database

      View table

      Table 1. 0 Recognition accuracy of different algorithms on FEI database

      Number of samples456789
      DSRC0.87340.90410.92330.94380.94590.9542
      Our algorithm +DSRC0.87380.90470.92340.94300.94650.9539
      CRC0.83000.86990.88520.90600.91350.9216
      Our algorithm +CRC0.85320.89030.90310.92200.92820.9363
      CFFR0.87090.89780.91530.91980.92740.9348
      Our algorithm +CFFR0.87650.90220.92280.92900.93620.9372
    • Table 1. Total CPU time used by different algorithms on ORL database

      View table

      Table 1. Total CPU time used by different algorithms on ORL database

      Number of samples23456
      Time by DSRC /s0.16360.18370.18930.18420.1673
      Time by our algorithm +DSRC /s0.14270.15800.16090.15310.1397
      Improvement /%12.814.015.016.916.5
      Time by CRC /s0.17530.18870.19530.18690.1681
      Time by our algorithm +CRC /s0.14850.16220.16330.15740.1440
      Improvement /%15.314.016.415.814.3
      Time by CFFR /s0.79120.93821.07801.23361.3746
      Time by our algorithm +CFFR /s0.60310.77520.82430.83040.9582
      Improvement /%23.717.423.532.730.3
    • Table 2. Recognition accuracy of different algorithms on ORL database

      View table

      Table 2. Recognition accuracy of different algorithms on ORL database

      Number of samples23456
      DSRC0.85860.91860.94690.96180.9699
      Our algorithm +DSRC0.85930.92100.94740.96370.9731
      CRC0.83310.89370.92480.94730.9569
      Our algorithm +CRC0.84290.89900.93080.94900.9597
      CFFR0.85250.91190.94120.95880.9675
      Our algorithm +CFFR0.85430.91490.94530.95930.9678
    • Table 3. Total CPU time used by different algorithms on GT database

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      Table 3. Total CPU time used by different algorithms on GT database

      Number of samples3456789
      Time by DSRC /s0.24410.25820.27220.27840.28380.27640.2562
      Time by our algorithm +DSRC /s0.20970.21980.22400.23300.24100.23310.2196
      Improvement /%14.114.917.716.315.115.714.3
      Time by CRC /s0.25740.27260.27740.29090.29010.28690.2771
      Time by our algorithm +CRC /s0.20530.22230.22940.24950.24790.24590.2377
      Improvement /%20.218.517.314.214.514.314.2
      Time by CFFR /s1.14951.32331.61041.89531.90212.16212.2487
      Time by our algorithm +CFFR /s0.79861.07431.23991.34401.49181.51371.4171
      Improvement /%30.118.823.029.121.630.037.0
    • Table 4. Recognition accuracy of different algorithms on GT database

      View table

      Table 4. Recognition accuracy of different algorithms on GT database

      Number of samples3456789
      DSRC0.60160.65640.69200.72290.75320.77350.7938
      Our algorithm +DSRC0.60250.65870.69400.72460.75450.77650.7944
      CRC0.55600.60520.64000.66770.68630.70910.7255
      Our algorithm +CRC0.57540.62750.66300.69140.70790.73160.7461
      CFFR0.60050.64220.67980.69600.71850.73510.7567
      Our algorithm +CFFR0.60260.65350.69190.71670.73550.75170.7695
    • Table 5. Total CPU time used by different algorithms on FERET database

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      Table 5. Total CPU time used by different algorithms on FERET database

      Number of samples2345
      Time by DSRC /s2.41902.38532.03321.5536
      Time by our algorithm +DSRC /s1.85431.97831.59011.2123
      Improvement /%23.317.121.821.0
      Time by CRC /s2.54012.44872.08051.6036
      Time by our algorithm +CRC /s1.93781.85011.62141.2563
      Improvement /%23.724.422.121.7
      Time by CFFR /s20.80629.56330.30925.937
      Time by our algorithm +CFFR /s11.69316.08017.34915.313
      Improvement /%43.845.642.841.0
    • Table 6. Recognition accuracy of different algorithms on FERET database

      View table

      Table 6. Recognition accuracy of different algorithms on FERET database

      Number of samples2345
      DSRC0.65800.61630.79000.8050
      Our algorithm +DSRC0.66160.61790.78800.8075
      CRC0.58500.50880.56330.7050
      Our algorithm +CRC0.59410.51940.58350.7218
      CFFR0.62500.54000.64000.7400
      Our algorithm +CFFR0.61870.53800.65900.7408
    • Table 7. Total CPU time used by different algorithms on AR database

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      Table 7. Total CPU time used by different algorithms on AR database

      Number of samples6810121416
      Time by DSRC /s7.44617.97009.80299.21908.73807.9250
      Time by our algorithm +DSRC /s4.87715.34896.42906.25806.25205.8150
      Improvement /%34.532.934.432.128.526.6
      Time by CRC /s7.61648.04599.97909.76419.04468.1810
      Time by our algorithm +CRC /s5.00305.37946.50996.62226.52536.0345
      Improvement /%34.333.134.732.227.826.2
      Time by CFFR /s99.132121.367135.631148.894153.322150.028
      Time by our algorithm +CFFR /s46.31457.44363.90471.82381.38082.083
      Improvement /%53.252.752.951.846.945.3
    • Table 8. Recognition accuracy of different algorithms on AR database

      View table

      Table 8. Recognition accuracy of different algorithms on AR database

      Number of samples6810121416
      DSRC0.66170.63750.59220.73630.89030.9192
      Our algorithm +DSRC0.67210.64510.60140.73780.89510.9200
      CRC0.64960.64720.60830.63450.82640.8692
      Our algorithm +CRC0.66000.65120.61310.66760.85480.8808
      CFFR0.70710.70420.66250.73990.89440.9167
      Our algorithm +CFFR0.69080.69630.65890.75540.90900.9267
    • Table 9. Total CPU time used by different algorithms on FEI database

      View table

      Table 9. Total CPU time used by different algorithms on FEI database

      Number of samples456789
      Time by DSRC /s0.82430.85121.08871.08850.97730.8304
      Time by our algorithm +DSRC /s0.44510.46410.59730.63690.57390.5003
      Improvement /%46.045.545.141.541.339.8
      Time by CRC /s0.83510.83351.07131.02010.92030.8090
      Time by our algorithm +CRC /s0.48620.47060.58710.59300.55580.4892
      Improvement /%41.843.545.241.939.639.5
      Time by CFFR /s4.94696.24307.22777.57827.39077.1898
      Time by our algorithm +CFFR /s2.21112.66023.01813.05233.14422.8095
      Improvement /%55.357.458.259.757.560.9
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    Wei Liu, Hongwei Ge. Fast Face Recognition Method Based on Sparse Representation[J]. Laser & Optoelectronics Progress, 2020, 57(18): 181024

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    Paper Information

    Category: Image Processing

    Received: Jan. 13, 2020

    Accepted: Feb. 24, 2020

    Published Online: Sep. 2, 2020

    The Author Email: Liu Wei (936917605@qq.com)

    DOI:10.3788/LOP57.181024

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