Contact nameAchraf Djerida
Contact email[email protected]
Contact university/companyshanghai jiaotong university,china.
Method's nameFSBE
ReferenceAchraf Djerida Robust background generation based on an effective frames selection method and an efficient background estimation procedure (FSBE) Journal Signal Processing: Image Communication DOI 10.1016/j.image.2019.06.001
Processing timeIt reaches 42 fps of size 360*240
Code is available onlineFalse
Parameters OP=0.25,ALF=10,AHF=60.

You can download the background estimation results of this method by clicking here.

Video AGE pEPs pCEPS MSSSIM PSNR CQM
skating 3.4964 0.0133 0.0021 0.9639 32.6782 33.8146
wetSnow 3.5902 0.0057 0.0022 0.9635 33.7833 34.2109
streetCornerAtNight 4.0028 0.0051 0.0028 0.9766 33.1310 34.3047
Hybrid 5.0512 0.0169 0.0001 0.9843 31.1015 31.6024
511 3.7414 0.0351 0.0019 0.9761 30.5804 32.2388
Blurred 3.1953 0.0050 0.0010 0.9882 31.8882 32.4592
CamouflageFgObjects 2.7628 0.0026 0.0000 0.9934 35.4212 35.7696
IntelligentRoom 3.0584 0.0044 0.0000 0.9915 34.5860 34.9651
PETS2006 3.0236 0.0055 0.0035 0.9821 33.6317 34.2344
IPPR2 4.2481 0.0032 0.0003 0.9747 33.2327 33.3834
MPEG4_40 2.7782 0.0168 0.0026 0.9782 32.5871 33.6330
ComplexBackground 6.2236 0.0316 0.0026 0.9839 28.9732 29.6639
fluidHighway 7.9442 0.0402 0.0239 0.9330 27.2747 27.4120
Intersection 2.7498 0.0017 0.0000 0.9867 36.1826 36.7326
I_SI_01 1.9073 0.0015 0.0001 0.9952 39.1006 39.5014
highway 4.5635 0.0209 0.0021 0.9831 30.5137 31.5301
Video AGE pEPs pCEPS MSSSIM PSNR CQM
overpass 10.0260 0.1404 0.0271 0.8261 24.2652 25.1883
canoe 14.8500 0.2677 0.0613 0.6506 20.7593 21.4343
advertisementBoard 1.8453 0.0029 0.0003 0.9814 37.9984 37.9817
fountain01 6.0915 0.0644 0.0126 0.9311 25.8926 27.0802
fountain02 6.7990 0.0462 0.0014 0.9504 28.4746 29.3467
fall 23.9054 0.3464 0.1190 0.7364 16.3222 17.4122
Video AGE pEPs pCEPS MSSSIM PSNR CQM
O_SM_04 6.4506 0.0477 0.0007 0.9645 28.5205 29.5599
boulevard 10.1060 0.1413 0.0283 0.9003 22.5280 23.8107
I_SM_04 5.8215 0.0531 0.0134 0.9357 23.9129 24.9267
I_MC_02 14.3470 0.1933 0.0845 0.7641 19.7769 20.9417
badminton 6.5668 0.0683 0.0370 0.8636 27.3765 28.2185
traffic 10.7239 0.1071 0.0677 0.8694 25.6710 26.7226
O_MC_02 12.5460 0.1773 0.0675 0.7741 21.2113 22.0340
sidewalk 21.9011 0.3070 0.1778 0.4751 16.6138 18.3083
CMU 5.0272 0.0349 0.0003 0.9899 29.8168 30.5228
Video AGE pEPs pCEPS MSSSIM PSNR CQM
Uturn 2.7258 0.0253 0.0150 0.9665 29.2159 29.9034
CaVignal 0.9964 0.0003 0.0000 0.9973 41.8731 42.2811
office 16.4024 0.2369 0.1353 0.8639 19.7669 20.5696
sofa 3.8068 0.0263 0.0173 0.9432 27.9022 28.9156
copyMachine 4.2840 0.0078 0.0010 0.9776 32.6525 33.5020
tramstop 2.4653 0.0082 0.0027 0.9936 34.5555 35.0937
UCF-traffic 2.0034 0.0131 0.0068 0.9628 32.0038 34.4069
streetCorner 7.7178 0.0417 0.0192 0.9567 25.5180 26.6610
AVSS2007 11.5900 0.1160 0.0840 0.8830 20.1106 21.2110
I_CA_01 4.7429 0.0191 0.0133 0.9623 28.0207 28.6336
I_CA_02 3.9541 0.0071 0.0006 0.9924 33.3210 34.0768
Candela_m1.10 3.5304 0.0187 0.0093 0.9688 29.4474 30.1990
I_MB_02 4.9876 0.0262 0.0166 0.9575 25.7055 26.8478
Teknomo 6.2894 0.0602 0.0075 0.9821 26.1280 27.2363
I_MB_01 5.6054 0.0274 0.0227 0.9828 27.8205 28.9774
busStation 4.3997 0.0036 0.0003 0.9847 33.1076 33.7125
Video AGE pEPs pCEPS MSSSIM PSNR CQM
People&Foliage 4.9011 0.0136 0.0010 0.9897 30.9975 31.2890
tramway 9.4790 0.1287 0.0601 0.9001 23.9765 25.4884
Crowded 7.2699 0.0475 0.0338 0.9580 28.2773 29.4703
groupCampus 7.9010 0.0893 0.0517 0.9148 26.9553 28.0035
IndianTraffic3 2.0343 0.0098 0.0048 0.9762 35.5626 36.7342
boulevardJam 2.3321 0.0104 0.0040 0.9653 33.8660 35.0117
HumanBody2 3.7548 0.0086 0.0010 0.9937 32.9508 33.2926
Board 5.5795 0.0300 0.0066 0.9340 29.7845 30.7618
Foliage 3.7463 0.0091 0.0008 0.9950 32.6995 32.8938
ICRA3 4.6841 0.0140 0.0038 0.9874 31.4670 31.7574
UCF-fishes 0.7435 0.0000 0.0000 0.9911 46.8018 48.1694
Video AGE pEPs pCEPS MSSSIM PSNR CQM
I_IL_01 7.3065 0.0020 0.0001 0.9924 29.8335 30.6723
I_IL_02 4.5513 0.0020 0.0006 0.9909 32.9142 33.7835
Dataset3Camera1 6.2455 0.0160 0.0032 0.9773 30.1704 31.0682
CameraParameter 1.0500 0.0001 0.0000 0.9970 44.0052 44.4921
Dataset3Camera2 6.6733 0.0177 0.0002 0.9817 29.2464 30.2773
cubicle 7.2266 0.0523 0.0197 0.9733 26.8334 27.5969
Video AGE pEPs pCEPS MSSSIM PSNR CQM
PedAndStorrowDrive3 1.9628 0.0060 0.0025 0.9966 35.0947 35.9997
PedAndStorrowDrive 7.5944 0.0798 0.0132 0.9671 25.8940 27.1562
BusStopMorning 6.1012 0.0360 0.0004 0.9787 29.2377 29.9504
Terrace 16.3164 0.2611 0.1595 0.9601 22.7646 23.7165
Dataset4Camera1 2.9413 0.0073 0.0005 0.9892 33.6399 34.0493
Video AGE pEPs pCEPS MSSSIM PSNR CQM
Toscana 7.5935 0.0621 0.0257 0.8579 21.5273 22.5033
pedestrians 1.9291 0.0006 0.0000 0.9928 38.4820 38.8545
DynamicBackground 9.0226 0.0962 0.0030 0.9524 25.5196 26.2648
peopleInShade 8.5379 0.0530 0.0042 0.9402 25.7640 26.7721
MIT 6.0468 0.0503 0.0039 0.9617 27.6090 28.7228
snowFall 2.6178 0.0003 0.0000 0.9575 37.0662 37.5355
TownCentre 3.8314 0.0087 0.0006 0.9697 32.8932 33.3980
CUHK_Square 5.1623 0.0378 0.0010 0.9672 28.9319 29.4720
NoisyNight 6.3360 0.0297 0.0012 0.9120 28.6722 29.5926
TwoLeaveShop1cor 3.8346 0.0088 0.0027 0.9660 28.9721 29.4773