Contact nameLucia Maddalena
Contact emaillucia.maddalena@cnr.it
Contact university/companyNational Research Council of Italy
Method's nameSC-SOBS-C4
ReferenceL. Maddalena and A.Petrosino "Extracting a Background Image by a Multi-modal Scene Background Model", Scene Background Modeling workshop (ICPR) 2016
Processing timen.a.
Code is available onlineTrue
Parameters default

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

Video AGE pEPs pCEPS MSSSIM PSNR CQM
skating 5.6320 0.0466 0.0041 0.9377 29.2082 30.6041
wetSnow 3.0697 0.0068 0.0036 0.9714 34.0169 34.6360
I_SI_01 2.4167 0.0021 0.0003 0.9934 37.3049 37.6561
streetCornerAtNight 3.0753 0.0015 0.0001 0.9756 35.6549 36.6898
Hybrid 6.4793 0.0393 0.0019 0.9724 29.0163 29.7318
511 5.5782 0.0589 0.0018 0.9553 27.2563 29.2562
Blurred 2.0878 0.0004 0.0000 0.9934 37.8907 38.2289
CamouflageFgObjects 3.5318 0.0071 0.0000 0.9865 33.4538 33.9125
IntelligentRoom 3.1792 0.0051 0.0000 0.9898 34.2802 34.6097
PETS2006 2.3503 0.0023 0.0014 0.9855 34.5353 35.0425
IPPR2 5.5299 0.0128 0.0019 0.9608 30.8834 31.1528
MPEG4_40 3.7605 0.0162 0.0008 0.9721 32.1461 32.9618
ComplexBackground 7.0881 0.0506 0.0019 0.9824 27.9203 28.6924
Intersection 2.9254 0.0020 0.0000 0.9850 35.7106 36.2560
fluidHighway 8.6974 0.0471 0.0341 0.9325 25.4197 25.3735
highway 4.3554 0.0205 0.0009 0.9706 30.1287 31.0594
Video AGE pEPs pCEPS MSSSIM PSNR CQM
overpass 9.3251 0.1343 0.0125 0.8502 23.9862 25.1282
advertisementBoard 2.4882 0.0125 0.0035 0.9726 34.4102 34.9123
canoe 16.2478 0.2943 0.0527 0.6519 20.0361 20.8419
fountain01 6.6516 0.0728 0.0153 0.9220 25.0403 26.3044
fountain02 7.4213 0.0641 0.0022 0.9410 27.5029 28.5246
fall 22.2338 0.3105 0.0946 0.7537 16.5080 17.6507
Video AGE pEPs pCEPS MSSSIM PSNR CQM
O_SM_04 6.7053 0.0558 0.0008 0.9617 28.0419 29.1119
boulevard 9.7795 0.1306 0.0174 0.8998 21.7477 23.1910
I_SM_04 3.8049 0.0338 0.0014 0.9752 29.8793 30.8414
I_MC_02 16.0080 0.2040 0.0802 0.7166 18.5718 19.7686
badminton 3.6988 0.0308 0.0084 0.9386 30.8739 31.8162
O_MC_02 15.5400 0.2163 0.0932 0.6927 19.3327 20.2794
traffic 6.3591 0.0603 0.0220 0.8940 27.8411 28.7015
CMU 5.7201 0.0470 0.0003 0.9845 28.7685 29.4897
sidewalk 22.5928 0.2888 0.1539 0.4996 15.9487 17.7138
Video AGE pEPs pCEPS MSSSIM PSNR CQM
Uturn 2.5621 0.0118 0.0021 0.9846 33.0499 33.7470
CaVignal 8.2622 0.0720 0.0103 0.8425 19.7386 21.2385
office 14.9117 0.1578 0.0659 0.8750 20.0260 20.9030
sofa 2.8351 0.0190 0.0099 0.9723 30.4970 31.3133
copyMachine 7.0296 0.0425 0.0315 0.9349 23.4190 24.9538
tramstop 2.8423 0.0042 0.0001 0.9941 35.0834 35.5089
UCF-traffic 1.9542 0.0102 0.0045 0.9672 32.8934 35.2169
streetCorner 8.9630 0.0687 0.0380 0.8933 21.6861 22.7686
AVSS2007 10.8835 0.0918 0.0645 0.8625 21.3609 22.2359
Teknomo 5.5800 0.0304 0.0068 0.9771 26.8542 27.8682
I_CA_02 9.5827 0.0936 0.0483 0.8154 20.1734 20.9279
Candela_m1.10 4.7006 0.0357 0.0178 0.9330 25.8468 26.5666
I_MB_02 6.2462 0.0389 0.0206 0.9293 23.3485 24.6099
I_MB_01 3.3474 0.0265 0.0219 0.9844 28.6448 29.8523
busStation 5.4672 0.0344 0.0195 0.9212 25.1635 26.3344
I_CA_01 4.9651 0.0414 0.0191 0.9214 27.0123 27.2646
Video AGE pEPs pCEPS MSSSIM PSNR CQM
People&Foliage 9.9988 0.1366 0.0674 0.9250 22.0790 22.6356
boulevardJam 6.7592 0.0797 0.0339 0.8752 26.8135 28.0968
Crowded 8.1924 0.0584 0.0363 0.9466 27.4525 28.7261
tramway 11.1102 0.1305 0.0414 0.8657 21.5709 23.1860
groupCampus 11.0996 0.1255 0.0633 0.8424 22.3057 23.1882
HumanBody2 3.5511 0.0060 0.0001 0.9936 33.5490 33.8002
Board 13.2993 0.1198 0.0615 0.5086 19.0239 20.3248
Foliage 4.8845 0.0101 0.0000 0.9903 31.7525 32.1566
UCF-fishes 1.7212 0.0007 0.0000 0.9722 39.4467 41.8900
ICRA3 5.6595 0.0406 0.0302 0.9211 22.6752 23.6216
IndianTraffic3 1.3731 0.0004 0.0001 0.9925 41.4154 42.1847
Video AGE pEPs pCEPS MSSSIM PSNR CQM
I_IL_01 5.9451 0.0276 0.0062 0.9832 29.9481 30.7976
I_IL_02 11.2684 0.1601 0.1106 0.9259 22.0919 22.8743
Dataset3Camera1 4.3142 0.0102 0.0008 0.9811 32.2211 32.9682
CameraParameter 30.9090 0.3493 0.2209 0.6086 13.4793 14.7779
Dataset3Camera2 3.6182 0.0133 0.0002 0.9857 32.4067 33.1004
cubicle 6.0993 0.0422 0.0058 0.9603 27.1668 27.9839
Video AGE pEPs pCEPS MSSSIM PSNR CQM
PedAndStorrowDrive3 2.9929 0.0116 0.0039 0.9928 31.0893 32.1009
PedAndStorrowDrive 6.7529 0.0600 0.0013 0.9774 27.4181 28.6879
BusStopMorning 6.1157 0.0416 0.0007 0.9850 28.6902 29.2283
Dataset4Camera1 3.8003 0.0109 0.0000 0.9909 32.5866 33.0526
Terrace 10.6573 0.0534 0.0044 0.9722 26.5234 27.4371
Video AGE pEPs pCEPS MSSSIM PSNR CQM
Toscana 4.9187 0.0448 0.0230 0.9483 28.5768 29.1880
CUHK_Square 5.0403 0.0361 0.0018 0.9639 29.2943 29.7716
pedestrians 1.9355 0.0017 0.0000 0.9924 37.8614 38.3609
NoisyNight 7.2033 0.0347 0.0012 0.8959 28.5172 29.3264
peopleInShade 7.8637 0.0286 0.0022 0.9711 28.3797 29.2700
DynamicBackground 9.0192 0.0967 0.0040 0.9512 26.0456 26.8005
snowFall 2.4548 0.0004 0.0000 0.9536 37.1976 37.7237
TwoLeaveShop1cor 4.0173 0.0152 0.0054 0.9621 29.4909 30.0231
MIT 6.2682 0.0602 0.0050 0.9571 27.3324 28.5621
TownCentre 4.2321 0.0119 0.0016 0.9603 32.3010 32.7872