TY - GEN
T1 - Locally orderless tracking
AU - Oron, Shaul
AU - Bar-Hillel, Aharon
AU - Levi, Dan
AU - Avidan, Shai
PY - 2012
Y1 - 2012
N2 - Locally Orderless Tracking (LOT) is a visual tracking algorithm that automatically estimates the amount of local (dis)order in the object. This lets the tracker specialize in both rigid and deformable objects on-line and with no prior assumptions. We provide a probabilistic model of the object variations over time. The model is implemented using the Earth Mover's Distance (EMD) with two parameters that control the cost of moving pixels and changing their color. We adjust these costs on-line during tracking to account for the amount of local (dis)order in the object. We show LOT's tracking capabilities on challenging video sequences, both commonly used and new, demonstrating performance comparable to state-of-the-art methods.
AB - Locally Orderless Tracking (LOT) is a visual tracking algorithm that automatically estimates the amount of local (dis)order in the object. This lets the tracker specialize in both rigid and deformable objects on-line and with no prior assumptions. We provide a probabilistic model of the object variations over time. The model is implemented using the Earth Mover's Distance (EMD) with two parameters that control the cost of moving pixels and changing their color. We adjust these costs on-line during tracking to account for the amount of local (dis)order in the object. We show LOT's tracking capabilities on challenging video sequences, both commonly used and new, demonstrating performance comparable to state-of-the-art methods.
UR - http://www.scopus.com/inward/record.url?scp=84866669517&partnerID=8YFLogxK
U2 - 10.1109/CVPR.2012.6247895
DO - 10.1109/CVPR.2012.6247895
M3 - ???researchoutput.researchoutputtypes.contributiontobookanthology.conference???
AN - SCOPUS:84866669517
SN - 9781467312264
T3 - Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
SP - 1940
EP - 1947
BT - 2012 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2012
T2 - 2012 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2012
Y2 - 16 June 2012 through 21 June 2012
ER -