TY - GEN
T1 - An online background subtraction algorithm using a contiguously weighted linear regression model
AU - Hu, Y.
AU - Sirlantzis, K.
AU - Howells, G.
AU - Ragot, N.
AU - Rodriguez, P.
N1 - Publisher Copyright:
© 2015 EURASIP.
PY - 2015/12/22
Y1 - 2015/12/22
N2 - In this paper, we propose a fast online background subtraction algorithm detecting a contiguous foreground. The proposed algorithm consists of a background model and a foreground model. The background model is a regression based low rank model. It seeks a low rank background subspace and represents the background as the linear combination of the basis spanning the subspace. The foreground model promotes the contiguity in the foreground detection. It encourages the foreground to be detected as whole regions rather than separated pixels. We formulate the background and foreground model into a contiguously weighted linear regression problem. This problem can be solved efficiently and it achieves an online scheme. The experimental comparison with most recent algorithms on the benchmark dataset demonstrates the high effectiveness of the proposed algorithm.
AB - In this paper, we propose a fast online background subtraction algorithm detecting a contiguous foreground. The proposed algorithm consists of a background model and a foreground model. The background model is a regression based low rank model. It seeks a low rank background subspace and represents the background as the linear combination of the basis spanning the subspace. The foreground model promotes the contiguity in the foreground detection. It encourages the foreground to be detected as whole regions rather than separated pixels. We formulate the background and foreground model into a contiguously weighted linear regression problem. This problem can be solved efficiently and it achieves an online scheme. The experimental comparison with most recent algorithms on the benchmark dataset demonstrates the high effectiveness of the proposed algorithm.
KW - contiguity
KW - online background subtraction
UR - http://www.scopus.com/inward/record.url?scp=84960827540&partnerID=8YFLogxK
U2 - 10.1109/EUSIPCO.2015.7362703
DO - 10.1109/EUSIPCO.2015.7362703
M3 - Conference contribution
AN - SCOPUS:84960827540
T3 - 2015 23rd European Signal Processing Conference, EUSIPCO 2015
SP - 1845
EP - 1849
BT - 2015 23rd European Signal Processing Conference, EUSIPCO 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 23rd European Signal Processing Conference, EUSIPCO 2015
Y2 - 31 August 2015 through 4 September 2015
ER -