Moving Object Detection in Dynamic Environment via Weighted Low-Rank Structured Sparse RPCA and Kalman Filtering

Table 1

Comparative analysis of quantitative metrics.

Algorithm	Video sequence	Re	Sp	FPR	FNR	PWC	Pr	F
MOG [27]	Boat	0.0371	0.99	0.01	0.0652	7.0438	0.2003	0.0626
	Canoe	0.0615	0.9966	0.0034	0.0564	5.6434	0.5192	0.1099
RPCA [11]	Boat	0.6967	0.9393	0.0607	0.0103	6.8723	0.2806	0.4001
	Canoe	0.2169	0.9633	0.367	0.0471	7.8995	0.2622	0.2374
WNNM [18]	Boat	0.6953	0.9392	0.0608	0.0104	6.8821	0.2800	0.3992
	Canoe	0.2204	0.9626	0.0374	0.0468	7.9458	0.2617	0.2393
Proposed	Boat	0.6782	0.9722	0.0484	0.0109	5.7352	0.3229	0.4375
	Canoe	0.2458	0.9652	0.0348	0.0453	7.5592	0.2980	0.2694