Clustering of Local Behaviour in Crowd Videos

Date

2014-04-25

Author

Öngün, Cihan
Temizel, Alptekin
Taşkaya Temizel, Tuğba

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Surveillance cameras are playing more important role in our daily life with the increasing number of human population and surveillance cameras. While there are a myriad of methods for video analysis, they are generally designed for low-density areas. Running of these algorithms in crowded areas would not give expected results and results in high number of false alarms giving rise to a need for different approaches for crowded area surveillance. Due to occlusions and images of individuals having a low resolution, holistic approaches have started to be preferred rather than detection and tracking of individuals. In this work, a method based on detection of regional behaviors in high density crowds is proposed. The method clusters the crowd behavior in different areas of the scene and can be used as a basis for anomaly detection.

Subject Keywords

Crowd Behavior Analysis, Video Surveillance Applications, Computer Vision

URI

https://hdl.handle.net/11511/55665

Conference Name

22nd IEEE Signal Processing and Communications Applications Conference (SIU)

Collections

Graduate School of Informatics, Conference / Seminar

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Citation Formats

C. Öngün, A. Temizel, and T. Taşkaya Temizel, “Clustering of Local Behaviour in Crowd Videos,” presented at the 22nd IEEE Signal Processing and Communications Applications Conference (SIU), Karadeniz Teknik Univ, Trabzon, TURKEY, 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/55665.