TY - GEN
T1 - Robust background subtraction using data fusion for real elevator scene
AU - Song, Taeyup
AU - Han, David K.
AU - Ko, Hanseok
PY - 2011
Y1 - 2011
N2 - This paper proposes a background subtraction technique robust in elevator environments. Sudden local illumination changes arise frequently in an elevator environment due to opening and closing of the elevator door as well as the inner walls of elevator being made of reflective materials. We present a novel method sequentially fusing a Gaussian mixture model for background subtraction, motion information and a spatial likelihood model based on textured features. Experimental results on real video data demonstrate effectiveness of the proposed approach.
AB - This paper proposes a background subtraction technique robust in elevator environments. Sudden local illumination changes arise frequently in an elevator environment due to opening and closing of the elevator door as well as the inner walls of elevator being made of reflective materials. We present a novel method sequentially fusing a Gaussian mixture model for background subtraction, motion information and a spatial likelihood model based on textured features. Experimental results on real video data demonstrate effectiveness of the proposed approach.
UR - http://www.scopus.com/inward/record.url?scp=80053965963&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=80053965963&partnerID=8YFLogxK
U2 - 10.1109/AVSS.2011.6027357
DO - 10.1109/AVSS.2011.6027357
M3 - Conference contribution
AN - SCOPUS:80053965963
SN - 9781457708459
T3 - 2011 8th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2011
SP - 392
EP - 397
BT - 2011 8th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2011
T2 - 2011 8th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2011
Y2 - 30 August 2011 through 2 September 2011
ER -