TY - GEN
T1 - Integrating pedestrian simulation, tracking and event detection for crowd analysis
AU - Butenuth, Matthias
AU - Burkert, Florian
AU - Schmidt, Florian
AU - Hinz, Stefan
AU - Hartmann, Dirk
AU - Kneidl, Angelika
AU - Borrmann, André
AU - Sirmacek, Beril
PY - 2011
Y1 - 2011
N2 - In this paper, an overall framework for crowd analysis is presented. Detection and tracking of pedestrians as well as detection of dense crowds is performed on image sequences to improve simulation models of pedestrian flows. Additionally, graph-based event detection is performed by using Hidden Markov Models on pedestrian trajectories utilizing knowledge from simulations. Experimental results show the benefit of our integrated framework using simulation and real-world data for crowd analysis.
AB - In this paper, an overall framework for crowd analysis is presented. Detection and tracking of pedestrians as well as detection of dense crowds is performed on image sequences to improve simulation models of pedestrian flows. Additionally, graph-based event detection is performed by using Hidden Markov Models on pedestrian trajectories utilizing knowledge from simulations. Experimental results show the benefit of our integrated framework using simulation and real-world data for crowd analysis.
UR - http://www.scopus.com/inward/record.url?scp=84856632164&partnerID=8YFLogxK
U2 - 10.1109/ICCVW.2011.6130237
DO - 10.1109/ICCVW.2011.6130237
M3 - Conference contribution
AN - SCOPUS:84856632164
SN - 9781467300629
T3 - Proceedings of the IEEE International Conference on Computer Vision
SP - 150
EP - 157
BT - 2011 IEEE International Conference on Computer Vision Workshops, ICCV Workshops 2011
T2 - 2011 IEEE International Conference on Computer Vision Workshops, ICCV Workshops 2011
Y2 - 6 November 2011 through 13 November 2011
ER -