DENSITY ESTIMATION IN CROWD VIDEOS

Date

2014-04-25

Author

Gunduz, Ayse Elvan
Taşkaya Temizel, Tuğba
Temizel, Alptekin

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

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In crowd surveillance systems, it is important to select the proper analysis algorithm considering the properties of the video content. The inappropriate algorithm selection may result in performance degradation and generation of false alarms. An important feature of crowd videos is the density of the crowd. While object detection and tracking based algorithms are feasible for low density crowds, holistic approaches are preferable for high density crowds. In this paper, we studied the problem of crowd density classification and reported the accuracy rates and execution times in comparison with the studies in the literature.

Subject Keywords

Crowd density estimation, Video surveillance applications, Computer vision

URI

https://hdl.handle.net/11511/55972

Conference Name

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

Collections

Graduate School of Informatics, Conference / Seminar

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Citation Formats

A. E. Gunduz, T. Taşkaya Temizel, and A. Temizel, “DENSITY ESTIMATION 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/11511/55972.