Contact nameBenjamin Laugraud
Contact emailblaugraud@ulg.ac.be
Contact university/companyUniversity of Liège
Method's nameLaBGen-OF
ReferenceB. Laugraud, M. Van Droogenbroeck « Is a Memoryless Motion Detection Truly Relevant for Background Generation with LaBGen? », Advanced Concepts for Intelligent Vision Systems (ACIVS), LNCS 10617, Pages 443-454, 2017
Processing timeTBD
Code is available onlineTrue
Web pagehttp://www.telecom.ulg.ac.be/labgen
Parameters S = 119, N = 8, P = 2, T = 4, A = DF

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

Video AGE pEPs pCEPS MSSSIM PSNR CQM
skating 3.8495 0.0198 0.0037 0.9609 31.9841 33.1984
wetSnow 2.5920 0.0026 0.0013 0.9783 36.6101 36.9786
I_SI_01 2.1101 0.0015 0.0002 0.9952 38.5733 39.0148
streetCornerAtNight 2.6570 0.0033 0.0024 0.9819 35.9344 37.0001
Hybrid 4.6012 0.0104 0.0000 0.9863 31.9712 32.4807
511 3.4434 0.0212 0.0003 0.9828 31.5917 33.1185
Blurred 1.1995 0.0000 0.0000 0.9982 43.0044 43.0016
CamouflageFgObjects 2.6262 0.0024 0.0000 0.9937 35.8833 36.1744
IntelligentRoom 2.8453 0.0019 0.0000 0.9932 35.6063 35.9113
PETS2006 1.8388 0.0026 0.0017 0.9899 34.6563 35.4184
IPPR2 5.3680 0.0064 0.0003 0.9689 31.4248 31.5270
MPEG4_40 3.9616 0.0200 0.0025 0.9662 31.1471 32.1534
ComplexBackground 5.6263 0.0202 0.0017 0.9850 29.7470 30.4422
Intersection 2.3691 0.0008 0.0000 0.9907 37.5172 38.0088
fluidHighway 11.1622 0.0559 0.0375 0.9390 25.1848 25.3454
highway 5.2243 0.0203 0.0008 0.9635 29.5064 30.4950
Video AGE pEPs pCEPS MSSSIM PSNR CQM
overpass 7.2635 0.0847 0.0074 0.9038 25.9428 26.9182
advertisementBoard 1.7604 0.0022 0.0005 0.9893 38.6184 39.0805
canoe 15.5547 0.2593 0.0623 0.6340 19.7236 20.1925
fountain01 5.9143 0.0592 0.0131 0.9315 25.9872 27.1630
fountain02 6.1902 0.0426 0.0028 0.9457 28.7554 29.6095
fall 23.7356 0.3390 0.1079 0.7258 16.1480 17.2208
Video AGE pEPs pCEPS MSSSIM PSNR CQM
O_SM_04 6.2194 0.0475 0.0005 0.9638 28.6254 29.6836
boulevard 11.9868 0.1590 0.0267 0.8719 20.2275 21.7778
I_SM_04 3.0991 0.0272 0.0003 0.9886 31.3441 32.1762
I_MC_02 14.7053 0.1846 0.0724 0.7475 18.9754 20.1964
badminton 1.8252 0.0053 0.0009 0.9883 37.3105 37.8042
O_MC_02 12.7972 0.1702 0.0626 0.7690 20.5108 21.3244
traffic 5.2832 0.0446 0.0057 0.9497 28.9493 29.7462
CMU 4.2025 0.0207 0.0001 0.9927 31.3829 32.0459
sidewalk 23.0500 0.2986 0.1725 0.4493 15.8218 17.5826
Video AGE pEPs pCEPS MSSSIM PSNR CQM
Uturn 4.9176 0.0378 0.0223 0.9384 24.4096 25.3859
CaVignal 1.5227 0.0004 0.0000 0.9964 40.4952 40.7226
office 9.9830 0.0449 0.0183 0.9514 24.5188 25.6112
sofa 2.3248 0.0043 0.0021 0.9948 36.5121 36.8640
copyMachine 4.2476 0.0138 0.0053 0.9627 28.8566 30.0838
tramstop 4.2395 0.0206 0.0001 0.9918 31.7719 32.3822
UCF-traffic 1.9372 0.0129 0.0067 0.9647 32.1842 34.3097
streetCorner 8.5837 0.0664 0.0400 0.8981 21.6835 22.8050
AVSS2007 11.0893 0.0925 0.0699 0.8783 21.3405 22.1769
Teknomo 5.4841 0.0280 0.0088 0.9823 26.4345 27.4526
I_CA_02 2.4027 0.0036 0.0001 0.9950 36.7153 37.2177
Candela_m1.10 2.2624 0.0027 0.0007 0.9908 34.9451 35.2476
I_MB_02 4.1029 0.0180 0.0139 0.9661 25.9174 27.0362
I_MB_01 4.1697 0.0000 0.0000 0.9963 34.5775 35.2742
busStation 4.3682 0.0075 0.0036 0.9799 31.5560 32.2876
I_CA_01 2.6580 0.0003 0.0000 0.9946 37.3604 37.4145
Video AGE pEPs pCEPS MSSSIM PSNR CQM
People&Foliage 3.1473 0.0011 0.0001 0.9945 35.1741 35.1775
boulevardJam 3.3109 0.0267 0.0105 0.9165 29.1868 30.4148
Crowded 7.8383 0.0529 0.0389 0.9552 27.8187 29.0724
tramway 7.2670 0.0687 0.0229 0.9143 23.8914 25.3991
groupCampus 7.3749 0.0675 0.0363 0.9275 27.7261 28.7510
HumanBody2 2.9173 0.0026 0.0001 0.9958 35.1385 35.4082
Board 5.6166 0.0295 0.0084 0.9455 29.6435 30.5267
Foliage 2.8703 0.0007 0.0000 0.9971 35.9942 36.1739
UCF-fishes 1.3677 0.0005 0.0000 0.9770 41.6859 43.2925
ICRA3 2.6912 0.0202 0.0116 0.9861 32.2273 32.8380
IndianTraffic3 1.6023 0.0006 0.0001 0.9943 40.4868 41.0655
Video AGE pEPs pCEPS MSSSIM PSNR CQM
I_IL_01 5.1334 0.0058 0.0000 0.9867 31.4032 32.1316
I_IL_02 6.0190 0.0317 0.0164 0.9754 29.2357 30.0125
Dataset3Camera1 8.8449 0.1693 0.1437 0.9332 25.2594 26.5554
CameraParameter 2.5397 0.0036 0.0000 0.9972 36.0581 36.4200
Dataset3Camera2 19.6355 0.4062 0.2597 0.9346 19.4204 20.9417
cubicle 7.1474 0.0616 0.0277 0.9653 25.6767 26.5529
Video AGE pEPs pCEPS MSSSIM PSNR CQM
PedAndStorrowDrive3 2.9268 0.0137 0.0009 0.9929 33.2168 33.9640
PedAndStorrowDrive 3.5195 0.0105 0.0005 0.9922 32.1467 33.1616
BusStopMorning 6.3929 0.0247 0.0015 0.9836 29.2204 30.0133
Dataset4Camera1 3.7162 0.0028 0.0000 0.9937 33.4884 34.0549
Terrace 4.8727 0.0054 0.0000 0.9829 32.3007 32.9621
Video AGE pEPs pCEPS MSSSIM PSNR CQM
Toscana 9.0752 0.1295 0.0988 0.8678 22.3347 23.1892
CUHK_Square 4.4371 0.0285 0.0010 0.9719 30.3463 30.8616
pedestrians 1.7611 0.0002 0.0000 0.9955 39.7146 40.0228
NoisyNight 5.4229 0.0258 0.0040 0.9177 29.5855 30.6929
peopleInShade 7.1549 0.0172 0.0072 0.9553 28.1995 28.9514
DynamicBackground 6.8785 0.0453 0.0007 0.9667 28.2601 28.8025
snowFall 2.2872 0.0003 0.0000 0.9627 37.9782 38.3110
TwoLeaveShop1cor 4.4175 0.0289 0.0179 0.9359 26.7617 27.4015
MIT 5.1428 0.0410 0.0034 0.9680 28.6220 29.7254
TownCentre 3.7612 0.0083 0.0022 0.9672 33.1564 33.3571