Contact nameDiego Ortego
Contact emaildiego.ortego@uam.es
Contact university/companyVideo Processing and Understanding Lab (VPULab), Universidad Autónoma de Madrid
Method's nameRMR
ReferenceD. Ortego, J. C. SanMiguel, J. M. Martínez, "Rejection based multipath reconstruction for background estimation in video sequences with stationary objects", Computer Vision and Image Understanding, vol. 147, pp. 23-37, 2016
Processing time~0.5 fps, unoptimized Matlab implementation
Code is available onlineFalse
Web pagehttp://www-vpu.eps.uam.es/publications/BE_RMR/
Parameters N=16 (32) if any image resolution dimension is lower (higher) than 400, ro=5, k=3

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

Video AGE pEPs pCEPS MSSSIM PSNR CQM
skating 9.8116 0.1238 0.0408 0.8365 22.4678 23.9420
wetSnow 3.3928 0.0046 0.0017 0.9575 34.1038 34.5768
I_SI_01 2.2996 0.0013 0.0001 0.9879 37.8160 38.2460
streetCornerAtNight 3.1218 0.0040 0.0027 0.9761 34.8402 35.9937
Hybrid 15.0338 0.2440 0.0940 0.7375 20.8193 21.5506
511 5.3709 0.0674 0.0036 0.9457 26.3268 28.3708
Blurred 2.9910 0.0169 0.0072 0.9699 30.4749 31.0951
CamouflageFgObjects 7.8394 0.0947 0.0561 0.9281 23.3538 24.0034
IntelligentRoom 3.0674 0.0060 0.0004 0.9907 34.3551 34.7119
PETS2006 2.4113 0.0008 0.0002 0.9893 37.7516 37.9057
IPPR2 4.6470 0.0077 0.0008 0.9689 32.1837 32.4051
MPEG4_40 4.2090 0.0316 0.0092 0.9508 28.3177 29.6966
ComplexBackground 9.0284 0.0763 0.0185 0.9355 22.6907 23.6944
Intersection 2.7770 0.0021 0.0000 0.9874 35.9753 36.5337
fluidHighway 9.6826 0.0479 0.0300 0.9359 25.7876 26.1176
highway 8.5028 0.0394 0.0017 0.9427 26.4460 27.6270
Video AGE pEPs pCEPS MSSSIM PSNR CQM
overpass 15.0570 0.2111 0.0746 0.6966 19.1595 19.9321
advertisementBoard 1.5575 0.0015 0.0000 0.9964 39.4799 39.7909
canoe 19.5947 0.3265 0.0856 0.6064 17.9059 18.4874
fountain01 7.1950 0.0821 0.0179 0.9022 23.9172 25.2021
fountain02 7.3068 0.0654 0.0082 0.9278 26.7854 27.5155
fall 23.0484 0.3225 0.0920 0.7611 16.2215 17.2962
Video AGE pEPs pCEPS MSSSIM PSNR CQM
O_SM_04 8.3818 0.0879 0.0073 0.9254 25.0287 26.2648
boulevard 13.4511 0.1842 0.0566 0.8198 19.5784 21.0043
I_SM_04 5.1498 0.0426 0.0112 0.9670 25.0802 26.2001
I_MC_02 15.4106 0.1895 0.0785 0.7366 18.6677 19.9169
badminton 8.4681 0.1227 0.0811 0.7365 23.8541 24.7652
O_MC_02 12.0355 0.1476 0.0470 0.8010 20.9252 21.8259
traffic 9.1391 0.1202 0.0656 0.7254 25.1776 26.1749
CMU 6.9662 0.0781 0.0051 0.9742 25.5719 26.4675
sidewalk 25.3898 0.3482 0.2089 0.3395 15.3927 17.0788
Video AGE pEPs pCEPS MSSSIM PSNR CQM
Uturn 2.6871 0.0234 0.0131 0.9680 29.3923 30.0893
CaVignal 1.2354 0.0002 0.0000 0.9962 40.7606 41.2068
office 10.4576 0.0685 0.0155 0.9716 25.8505 26.6531
sofa 2.2413 0.0034 0.0016 0.9922 36.8434 37.1986
copyMachine 6.1841 0.0259 0.0136 0.9667 29.4652 30.4191
tramstop 4.0753 0.0184 0.0009 0.9884 31.2124 31.8158
UCF-traffic 1.9553 0.0115 0.0058 0.9654 32.6634 34.9973
streetCorner 5.2663 0.0156 0.0061 0.9818 29.3515 30.2434
AVSS2007 9.2767 0.0663 0.0513 0.9094 20.3096 21.3404
Teknomo 5.7299 0.0363 0.0063 0.9716 26.8961 27.9404
I_CA_02 5.1246 0.0388 0.0212 0.9639 26.4139 27.1210
Candela_m1.10 2.5884 0.0032 0.0000 0.9949 36.1408 36.1531
I_MB_02 3.4959 0.0050 0.0027 0.9840 34.1510 34.7315
I_MB_01 3.0618 0.0033 0.0011 0.9859 34.2275 35.0617
busStation 3.1366 0.0134 0.0053 0.9631 30.3210 31.4297
I_CA_01 3.2538 0.0076 0.0015 0.9655 34.1952 34.4539
Video AGE pEPs pCEPS MSSSIM PSNR CQM
People&Foliage 33.3270 0.3313 0.2906 0.5342 12.2052 13.3842
boulevardJam 4.8947 0.0388 0.0128 0.9282 29.2511 30.5310
Crowded 7.9463 0.0574 0.0341 0.9423 27.5218 28.7301
tramway 14.7508 0.2043 0.0482 0.8268 19.4502 20.9041
groupCampus 22.6134 0.2826 0.1673 0.4652 16.0017 16.8798
HumanBody2 13.6012 0.1138 0.0731 0.7685 16.9066 18.0912
Board 7.0139 0.0401 0.0079 0.8337 28.3130 29.3061
Foliage 49.6680 0.7049 0.5006 -0.0870 12.1684 12.9637
UCF-fishes 1.0457 0.0005 0.0002 0.9806 42.7483 44.4171
ICRA3 10.1774 0.1915 0.1633 0.9019 21.7150 22.5227
IndianTraffic3 3.3920 0.0361 0.0240 0.9417 30.6872 32.1454
Video AGE pEPs pCEPS MSSSIM PSNR CQM
I_IL_01 9.7467 0.1207 0.1000 0.9437 25.4816 26.6659
I_IL_02 9.7454 0.1407 0.1064 0.9408 23.4406 24.4845
Dataset3Camera1 7.7915 0.0405 0.0112 0.9162 28.0960 29.1434
CameraParameter 1.2104 0.0004 0.0000 0.9910 41.7392 42.5813
Dataset3Camera2 7.1402 0.0365 0.0034 0.9310 28.0124 29.0944
cubicle 7.4869 0.0547 0.0210 0.9685 26.0071 26.8601
Video AGE pEPs pCEPS MSSSIM PSNR CQM
PedAndStorrowDrive3 4.2348 0.0398 0.0040 0.9779 28.7352 29.7659
PedAndStorrowDrive 26.0220 0.5813 0.3349 0.7422 18.2712 19.7232
BusStopMorning 5.9804 0.0372 0.0010 0.9793 28.4728 29.1260
Dataset4Camera1 4.9501 0.0097 0.0005 0.9920 31.4085 32.0248
Terrace 25.0421 0.6056 0.4450 0.8662 18.7667 19.7293
Video AGE pEPs pCEPS MSSSIM PSNR CQM
Toscana 6.9606 0.0554 0.0359 0.8981 22.9475 23.7080
CUHK_Square 6.7243 0.0662 0.0074 0.9359 25.3910 26.0475
pedestrians 1.6400 0.0004 0.0000 0.9951 39.7712 40.1219
NoisyNight 6.4003 0.0382 0.0095 0.8929 27.5206 28.7724
peopleInShade 9.2772 0.0668 0.0166 0.9568 26.8045 27.7174
DynamicBackground 14.5281 0.2038 0.0400 0.8664 19.8128 20.6954
snowFall 2.5053 0.0008 0.0001 0.9538 36.9386 37.4674
TwoLeaveShop1cor 4.8674 0.0256 0.0155 0.9269 25.6549 26.3624
MIT 6.5953 0.0680 0.0092 0.9417 25.6235 26.9524
TownCentre 4.5600 0.0156 0.0028 0.9616 30.4174 31.0549