TY - CONF
T1 - Background Subtraction in Video Using Recursive Mixture Models, Spatio-Temporal Filtering and Shadow Removal
AU - Chen, Zezhi
AU - Pears, Nick
AU - Freeman, Michael
AU - Austin, Jim
PY - 2009
Y1 - 2009
N2 - We describe our approach to segmenting moving objects from the color video data supplied by a nominally stationary camera. There are two main contributions in our work. The first contribution augments Zivkovic and Heijden’s recursively updated Gaussian mixture model approach, with a multi-dimensional Gaussian kernel spatio-temporal smoothing transform. We show that this improves the segmentation performance of the original approach, particularly in adverse imaging conditions, such as when there is camera vibration. Our second contribution is to present a comprehensive comparative evaluation of shadow and highlight detection appoaches, which is an essential component of background subtraction in unconstrained outdoor scenes. A comparative evelaution of these approaches over different color-spaces is currently lacking in the literature. We show that both segmentation and shadow removal performs best when we use RGB color spaces.
AB - We describe our approach to segmenting moving objects from the color video data supplied by a nominally stationary camera. There are two main contributions in our work. The first contribution augments Zivkovic and Heijden’s recursively updated Gaussian mixture model approach, with a multi-dimensional Gaussian kernel spatio-temporal smoothing transform. We show that this improves the segmentation performance of the original approach, particularly in adverse imaging conditions, such as when there is camera vibration. Our second contribution is to present a comprehensive comparative evaluation of shadow and highlight detection appoaches, which is an essential component of background subtraction in unconstrained outdoor scenes. A comparative evelaution of these approaches over different color-spaces is currently lacking in the literature. We show that both segmentation and shadow removal performs best when we use RGB color spaces.
UR - http://www.scopus.com/inward/record.url?scp=72449179513&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-10520-3_109
DO - 10.1007/978-3-642-10520-3_109
M3 - Paper
SP - 1141
EP - 1150
ER -