TY - GEN
T1 - Learning traffic patterns at intersections by spectral clustering of motion trajectories
AU - Atev, Stefan
AU - Masoud, Osama
AU - Papanikolopoulos, Nikos
PY - 2006
Y1 - 2006
N2 - We address the problem of automatically learning the layout of a traffic intersection from trajectories of vehicles obtained by a vision tracking system. We present a similarity measure which is suitable for use with spectral clustering in problems that emphasize spatial distinctions between vehicle trajectories. The robustness of the method to small perturbations and its sensitivity to the choice of parameters are evaluated using real-world data.
AB - We address the problem of automatically learning the layout of a traffic intersection from trajectories of vehicles obtained by a vision tracking system. We present a similarity measure which is suitable for use with spectral clustering in problems that emphasize spatial distinctions between vehicle trajectories. The robustness of the method to small perturbations and its sensitivity to the choice of parameters are evaluated using real-world data.
UR - http://www.scopus.com/inward/record.url?scp=34250630167&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=34250630167&partnerID=8YFLogxK
U2 - 10.1109/IROS.2006.282362
DO - 10.1109/IROS.2006.282362
M3 - Conference contribution
AN - SCOPUS:34250630167
SN - 142440259X
SN - 9781424402595
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 4851
EP - 4856
BT - 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2006
T2 - 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2006
Y2 - 9 October 2006 through 15 October 2006
ER -