Contact nameCristiano Massaroni
Contact emailmassaroni@di.uniroma1.it
Contact university/companySapienza University of Rome
Method's nameABM
ReferenceDanilo Avola, Marco Bernardi, Luigi Cinque, Gian Luca Foresti, Cristiano Massaroni "Adaptive bootstrapping management by keypoint clustering for background initialization", Pattern Recognition Letters Volume 100, 1 December 2017, Pages 110-116 (www.sciencedirect.com/science/article/pii/S0167865517303975)
Processing time30 fps for 320x240
Code is available onlineFalse
Parameters eps = 60, minPts = 3, tau = 2, beta = 0.75, gamma = 0.76

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

Video AGE pEPs pCEPS MSSSIM PSNR CQM
skating 5.7502 0.0573 0.0081 0.9198 27.2699 28.5965
wetSnow 6.5565 0.0533 0.0357 0.8846 25.1401 26.0963
I_SI_01 2.6296 0.0018 0.0002 0.9918 36.6506 37.1060
streetCornerAtNight 6.4200 0.0666 0.0452 0.9412 27.4838 28.9687
Hybrid 8.3822 0.0724 0.0105 0.9380 26.2731 26.8855
511 6.1224 0.0628 0.0032 0.9407 26.5925 28.5767
Blurred 2.4574 0.0018 0.0004 0.9906 36.5219 36.8815
CamouflageFgObjects 5.6603 0.0424 0.0172 0.9440 26.5547 27.1699
IntelligentRoom 3.6757 0.0066 0.0000 0.9879 33.4476 33.8018
PETS2006 2.2135 0.0001 0.0000 0.9894 38.5228 38.7412
IPPR2 2.3772 0.0032 0.0003 0.9879 35.7601 35.9857
MPEG4_40 2.0250 0.0184 0.0037 0.9786 31.7160 33.0194
ComplexBackground 9.1912 0.0869 0.0244 0.9436 23.6447 24.5316
Intersection 3.0620 0.0028 0.0000 0.9847 35.2577 35.8135
fluidHighway 8.6241 0.0538 0.0367 0.9203 25.0304 25.1034
highway 4.2512 0.0282 0.0013 0.9753 29.1670 30.2071
Video AGE pEPs pCEPS MSSSIM PSNR CQM
overpass 7.7060 0.0902 0.0092 0.9210 25.0658 26.0500
advertisementBoard 2.0773 0.0012 0.0003 0.9940 36.9781 37.2810
canoe 15.7454 0.2890 0.0403 0.6659 20.3344 22.9912
fountain01 2.6628 0.0209 0.0008 0.9741 32.3375 33.2972
fountain02 6.5797 0.0541 0.0066 0.9349 28.1339 29.0249
fall 25.2002 0.3339 0.1180 0.7075 15.3204 16.4358
Video AGE pEPs pCEPS MSSSIM PSNR CQM
O_SM_04 6.1060 0.0455 0.0015 0.9677 28.5303 29.5772
boulevard 11.4377 0.1573 0.0283 0.8776 20.6235 22.0462
I_SM_04 4.7375 0.0307 0.0057 0.9774 26.7598 27.9289
I_MC_02 17.9819 0.2403 0.1067 0.6576 17.8648 19.1012
badminton 7.7833 0.0887 0.0397 0.7872 23.9886 24.9043
O_MC_02 14.7574 0.1993 0.0706 0.7276 19.8427 20.7476
traffic 13.2766 0.1344 0.0383 0.8424 21.3766 22.3528
CMU 5.7161 0.0471 0.0007 0.9870 28.5525 29.3026
sidewalk 23.2358 0.3078 0.1518 0.4900 15.9427 17.5988
Video AGE pEPs pCEPS MSSSIM PSNR CQM
Uturn 4.9317 0.0383 0.0188 0.9398 25.6198 26.5554
CaVignal 2.3120 0.0040 0.0013 0.9950 34.8765 35.5245
office 12.7611 0.2110 0.1229 0.9490 23.1509 24.5832
sofa 3.8991 0.0193 0.0101 0.9820 31.4086 32.0522
copyMachine 5.5362 0.0126 0.0076 0.9637 29.6921 30.7402
tramstop 5.6281 0.0308 0.0148 0.9734 26.4353 27.3132
UCF-traffic 3.0784 0.0285 0.0136 0.9350 29.1733 31.6032
streetCorner 4.7727 0.0135 0.0053 0.9774 29.5370 30.4455
AVSS2007 9.6720 0.0810 0.0585 0.8809 21.6609 22.5576
Teknomo 6.9839 0.0507 0.0132 0.9551 24.7641 25.8240
I_CA_02 4.8815 0.0436 0.0272 0.9374 26.7709 27.7076
Candela_m1.10 3.9683 0.0098 0.0007 0.9887 32.7263 32.9212
I_MB_02 3.7068 0.0333 0.0210 0.9658 27.1779 28.1220
I_MB_01 6.0684 0.0166 0.0148 0.9777 22.8437 24.2278
busStation 6.5147 0.0473 0.0297 0.9128 24.4467 25.5588
I_CA_01 6.0730 0.0256 0.0193 0.9458 26.4278 27.2716
Video AGE pEPs pCEPS MSSSIM PSNR CQM
People&Foliage 9.6096 0.1203 0.0776 0.8596 20.6726 21.3812
boulevardJam 7.6215 0.0979 0.0477 0.7546 24.7166 26.0921
Crowded 10.1759 0.0939 0.0577 0.8714 25.5205 26.7152
tramway 13.0065 0.1449 0.0498 0.7831 19.5136 21.1087
groupCampus 27.3375 0.3342 0.2215 0.3253 14.6726 15.5122
HumanBody2 6.5543 0.0466 0.0100 0.9771 26.0702 26.5190
Board 13.9757 0.1477 0.0668 0.7647 20.3477 21.4077
Foliage 13.5276 0.1755 0.0798 0.8557 20.4735 21.2559
UCF-fishes 3.0261 0.0240 0.0099 0.8741 30.4693 32.7294
ICRA3 14.5330 0.3164 0.2680 0.9388 19.6817 20.6951
IndianTraffic3 3.8790 0.0414 0.0234 0.9101 28.7358 29.9640
Video AGE pEPs pCEPS MSSSIM PSNR CQM
I_IL_01 11.4432 0.1288 0.1082 0.9435 24.7571 25.9619
I_IL_02 5.6320 0.0397 0.0208 0.9834 29.4165 30.2467
Dataset3Camera1 6.7514 0.0559 0.0402 0.9495 27.1977 28.2091
CameraParameter 26.8946 0.2118 0.1774 0.7026 12.5673 13.9097
Dataset3Camera2 13.3738 0.2386 0.1695 0.9541 21.9341 23.2567
cubicle 3.3538 0.0104 0.0035 0.9830 33.3134 33.8041
Video AGE pEPs pCEPS MSSSIM PSNR CQM
PedAndStorrowDrive3 4.1061 0.0241 0.0010 0.9843 30.9053 31.7135
PedAndStorrowDrive 4.9002 0.0384 0.0069 0.9813 27.5501 28.8003
BusStopMorning 6.3938 0.0392 0.0024 0.9753 28.0470 28.7058
Dataset4Camera1 2.9197 0.0061 0.0000 0.9908 34.4815 34.8107
Terrace 5.8851 0.0129 0.0011 0.9602 30.6343 31.3279
Video AGE pEPs pCEPS MSSSIM PSNR CQM
Toscana 8.5494 0.0671 0.0465 0.8787 21.4364 22.2481
CUHK_Square 12.6833 0.1206 0.0515 0.8334 18.1330 19.1192
pedestrians 2.1192 0.0027 0.0002 0.9858 37.0673 37.3778
NoisyNight 5.7869 0.0185 0.0002 0.9031 30.1026 30.6602
peopleInShade 8.5597 0.0612 0.0186 0.9668 27.0625 27.8934
DynamicBackground 15.7404 0.2096 0.0495 0.8399 18.5263 19.4625
snowFall 2.9028 0.0052 0.0016 0.9492 34.8799 35.4364
TwoLeaveShop1cor 4.0212 0.0204 0.0107 0.9723 29.5718 30.0838
MIT 10.0610 0.1108 0.0323 0.8854 21.2224 22.6088
TownCentre 7.1480 0.0477 0.0267 0.8861 24.5382 25.2181