TY - GEN
T1 - Background subtraction under sudden illumination change
AU - Sajid, Hasan
AU - Cheung, Sen Ching Samson
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/11/14
Y1 - 2014/11/14
N2 - In this paper, we propose a Multiple Background Model based Background Subtraction (MB2S) algorithm that is robust against sudden illumination changes in indoor environment. It uses multiple background models of expected illumination changes followed by both pixel and frame based background subtraction on both RGB and YCbCr color spaces. The masks generated after processing these input images are then combined in a framework to classify background and foreground pixels. Evaluation of proposed approach on publicly available test sequences show higher precision and recall than other state-of-the-art algorithms.
AB - In this paper, we propose a Multiple Background Model based Background Subtraction (MB2S) algorithm that is robust against sudden illumination changes in indoor environment. It uses multiple background models of expected illumination changes followed by both pixel and frame based background subtraction on both RGB and YCbCr color spaces. The masks generated after processing these input images are then combined in a framework to classify background and foreground pixels. Evaluation of proposed approach on publicly available test sequences show higher precision and recall than other state-of-the-art algorithms.
UR - https://www.scopus.com/pages/publications/84914170924
UR - https://www.scopus.com/pages/publications/84914170924#tab=citedBy
U2 - 10.1109/MMSP.2014.6958814
DO - 10.1109/MMSP.2014.6958814
M3 - Conference contribution
AN - SCOPUS:84914170924
T3 - 2014 IEEE International Workshop on Multimedia Signal Processing, MMSP 2014
BT - 2014 IEEE International Workshop on Multimedia Signal Processing, MMSP 2014
T2 - 2014 16th IEEE International Workshop on Multimedia Signal Processing, MMSP 2014
Y2 - 22 September 2014 through 24 September 2014
ER -