Method RGB-SOBS on the SBM-RGBD dataset

Contact name: Lucia Maddalena

Contact email: lucia.maddalena@cnr.it

Contact Institution: National Research Council of Italy

Method processing time: ~4 fps for a 640x480 video (including I/O) with C++ code running on a Intel Core i5 2.7GHz

Note: Uses only RGB data

Reference: L. Maddalena, A. Petrosino, The SOBS algorithm: What are the limits?, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp.21-26, 16-21 June 2012.

Get all result files: here.

A) Sequence-by-sequence results

Name	Recall	Specificity	FPR	FNR	PWC	Precision	F-Measure
Bootstrapping
BootStrapping_ds	0.9155	0.9942	0.0058	0.0845	1.3206	0.9423	0.9287
adl24cam0	0.7030	0.9917	0.0083	0.2970	2.5818	0.8454	0.7676
bear_front	0.6026	0.9588	0.0412	0.3974	13.4976	0.8396	0.7016
fall01cam0	0.8935	0.9807	0.0193	0.1065	2.4133	0.7316	0.8045
fall20cam0	0.8969	0.9814	0.0186	0.1031	2.2970	0.7234	0.8008
ColorCamouflage
Cespatx_ds	0.8111	0.9997	0.0003	0.1889	0.4202	0.9797	0.8875
Hallway	0.5782	0.9629	0.0371	0.4218	5.7161	0.4624	0.5138
colorCam1	0.1045	0.9997	0.0003	0.8955	20.0782	0.9906	0.1891
colorCam2	0.2304	0.9443	0.0557	0.7696	37.9469	0.7745	0.3551
DepthCamouflage
DCamSeq1	0.9969	0.9770	0.0230	0.0031	2.1855	0.7197	0.8359
DCamSeq2	0.9942	0.9912	0.0088	0.0058	0.8676	0.8378	0.9093
Despatx_ds	0.9001	0.9985	0.0015	0.0999	1.0473	0.9831	0.9397
Wall	0.9990	0.9757	0.0243	0.0010	2.2233	0.8011	0.8892
IlluminationChanges
ChairBox	0.7684	0.9986	0.0014	0.2316	2.6509	0.9848	0.8633
Ls_ds	0.0000	0.9212	0.0788	0.0000	7.8775	0.0000	0.0000
TimeOfDay_ds	0.0000	0.9789	0.0211	0.0000	2.1150	0.0000	0.0000
genSeq1	0.9781	0.9875	0.0125	0.0219	1.3655	0.9188	0.9475
IntermittentMotion
Shelves	0.9023	0.9294	0.0706	0.0977	7.1144	0.2033	0.3319
Sleeping_ds	0.9020	0.9339	0.0661	0.0980	7.2499	0.7744	0.8334
abandoned1	0.9785	0.9778	0.0222	0.0215	2.2179	0.5309	0.6883
abandoned2	0.9909	0.7622	0.2378	0.0091	21.0108	0.3650	0.5335
movedBackground1	0.9510	0.9640	0.0360	0.0490	3.6208	0.2838	0.4371
movedBackground2	0.8344	0.8499	0.1501	0.1656	15.1125	0.2753	0.4140
OutOfRange
MultiPeople1	0.9586	0.9702	0.0298	0.0414	3.0693	0.7321	0.8302
MultiPeople2	0.9832	0.9945	0.0055	0.0168	0.6429	0.9407	0.9615
TopViewLab1	0.7687	0.9943	0.0057	0.2313	1.3208	0.8229	0.7949
TopViewLab2	0.9067	0.9964	0.0036	0.0933	0.7012	0.9107	0.9087
TopViewLab3	0.8339	0.9927	0.0073	0.1661	1.0710	0.7120	0.7681
Shadows
Shadows_ds	0.7565	0.9963	0.0037	0.2435	1.8413	0.9311	0.8347
fall01cam1	0.9789	0.9966	0.0034	0.0211	0.4480	0.9513	0.9649
genSeq2	0.9768	0.9903	0.0097	0.0232	1.1179	0.9269	0.9512
shadows1	0.9723	0.9794	0.0206	0.0277	2.1610	0.8849	0.9266
shadows2	0.9952	0.9776	0.0224	0.0048	1.9960	0.8759	0.9318

B) Average results for each category

Name	Recall	Specificity	FPR	FNR	PWC	Precision	F-Measure
Bootstrapping	0.8023	0.9814	0.0186	0.1977	4.4221	0.8165	0.8007
ColorCamouflage	0.4310	0.9767	0.0233	0.5690	16.0404	0.8018	0.4864
DepthCamouflage	0.9725	0.9856	0.0144	0.0275	1.5809	0.8354	0.8935
IlluminationChanges	0.4366	0.9715	0.0285	0.0634	3.5022	0.4759	0.4527
IntermittentMotion	0.9265	0.9028	0.0972	0.0735	9.3877	0.4054	0.5397
OutOfRange	0.8902	0.9896	0.0104	0.1098	1.3610	0.8237	0.8527
Shadows	0.9359	0.9881	0.0119	0.0641	1.5128	0.9140	0.9218
AVG.	0.7707	0.9708	0.0292	0.1578	5.4010	0.7247	0.7068