TY - GEN
T1 - Event based surveillance video synopsis using trajectory kinematics descriptors
AU - Wang, Wei Cheng
AU - Chung, Pau Choo
AU - Huang, Chun Rong
AU - Huang, Wei Yun
N1 - Publisher Copyright:
© 2017 MVA Organization All Rights Reserved.
PY - 2017/7/19
Y1 - 2017/7/19
N2 - Video synopsis has been shown its promising performance in visual surveillance, but the rearranged foreground objects may disorderly occlude to each other which makes end users hard to identify the targets. In this paper, a novel event based video synopsis method is proposed by using the clustering results of trajectories of foreground objects. To represent the kinematic events of each trajectory, trajectory kinematics descriptors are applied. Then, affinity propagation is used to cluster trajectories with similar kinematic events. Finally, each kinematic event group is used to generate an event based synopsis video. As shown in the experiments, the generated event based synopsis videos can effectively and efficiently reduce the lengths of the surveillance videos and are much clear for browsing compared to the states-of-the-art video synopsis methods.
AB - Video synopsis has been shown its promising performance in visual surveillance, but the rearranged foreground objects may disorderly occlude to each other which makes end users hard to identify the targets. In this paper, a novel event based video synopsis method is proposed by using the clustering results of trajectories of foreground objects. To represent the kinematic events of each trajectory, trajectory kinematics descriptors are applied. Then, affinity propagation is used to cluster trajectories with similar kinematic events. Finally, each kinematic event group is used to generate an event based synopsis video. As shown in the experiments, the generated event based synopsis videos can effectively and efficiently reduce the lengths of the surveillance videos and are much clear for browsing compared to the states-of-the-art video synopsis methods.
UR - https://www.scopus.com/pages/publications/85027861884
UR - https://www.scopus.com/pages/publications/85027861884#tab=citedBy
U2 - 10.23919/MVA.2017.7986848
DO - 10.23919/MVA.2017.7986848
M3 - Conference contribution
AN - SCOPUS:85027861884
T3 - Proceedings of the 15th IAPR International Conference on Machine Vision Applications, MVA 2017
SP - 250
EP - 253
BT - Proceedings of the 15th IAPR International Conference on Machine Vision Applications, MVA 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 15th IAPR International Conference on Machine Vision Applications, MVA 2017
Y2 - 8 May 2017 through 12 May 2017
ER -