Event based surveillance video synopsis using trajectory kinematics descriptors

Wei Cheng Wang, Pau Choo Chung, Chun Rong Huang, Wei Yun Huang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationProceedings of the 15th IAPR International Conference on Machine Vision Applications, MVA 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages250-253
Number of pages4
ISBN (Electronic)9784901122160
DOIs
Publication statusPublished - 2017 Jul 19
Event15th IAPR International Conference on Machine Vision Applications, MVA 2017 - Nagoya, Japan
Duration: 2017 May 82017 May 12

Publication series

NameProceedings of the 15th IAPR International Conference on Machine Vision Applications, MVA 2017

Other

Other15th IAPR International Conference on Machine Vision Applications, MVA 2017
CountryJapan
CityNagoya
Period17-05-0817-05-12

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computer Vision and Pattern Recognition

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