Suspicious behavior detection in public transport by fusion of low-level video descriptors

Dejan Arsić; Björn Schuller; Gerhard Rigoll

doi:10.1109/icme.2007.4285076

Suspicious behavior detection in public transport by fusion of low-level video descriptors

Dejan Arsić, Björn Schuller, Gerhard Rigoll

Technical University of Munich

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

15 Scopus citations

Abstract

Recently great interest has been shown in the visual surveillance of public transportation systems. The challenge is the automated analysis of passenger's behaviors with a set of visual low-level features, which can be extracted robustly. On a set of global motion features computed in different parts of the image, here the complete image, the face and skin color regions, a classification with Support Vector Machines is performed. Test-runs on a database of aggressive, cheerful, intoxicated, nervous, neutral and tired behavior in an airplane situation show promising results.

Original language	English
Title of host publication	Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007
Publisher	IEEE Computer Society
Pages	2018-2021
Number of pages	4
ISBN (Print)	1424410177, 9781424410170
DOIs	https://doi.org/10.1109/icme.2007.4285076
State	Published - 2007
Event	IEEE International Conference onMultimedia and Expo, ICME 2007 - Beijing, China Duration: 2 Jul 2007 → 5 Jul 2007

Publication series

Name	Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007

Conference

Conference	IEEE International Conference onMultimedia and Expo, ICME 2007
Country/Territory	China
City	Beijing
Period	2/07/07 → 5/07/07

Keywords

Behavior detection
Feature fusion
Low level features
Video surveillance

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10.1109/icme.2007.4285076

Cite this

Arsić, D., Schuller, B., & Rigoll, G. (2007). Suspicious behavior detection in public transport by fusion of low-level video descriptors. In Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007 (pp. 2018-2021). Article 4285076 (Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007). IEEE Computer Society. https://doi.org/10.1109/icme.2007.4285076

Arsić, Dejan ; Schuller, Björn ; Rigoll, Gerhard. / Suspicious behavior detection in public transport by fusion of low-level video descriptors. Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007. IEEE Computer Society, 2007. pp. 2018-2021 (Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007).

@inproceedings{e0a139df5d97408ea29bd170463dcf26,

title = "Suspicious behavior detection in public transport by fusion of low-level video descriptors",

abstract = "Recently great interest has been shown in the visual surveillance of public transportation systems. The challenge is the automated analysis of passenger's behaviors with a set of visual low-level features, which can be extracted robustly. On a set of global motion features computed in different parts of the image, here the complete image, the face and skin color regions, a classification with Support Vector Machines is performed. Test-runs on a database of aggressive, cheerful, intoxicated, nervous, neutral and tired behavior in an airplane situation show promising results.",

keywords = "Behavior detection, Feature fusion, Low level features, Video surveillance",

author = "Dejan Arsi{\'c} and Bj{\"o}rn Schuller and Gerhard Rigoll",

year = "2007",

doi = "10.1109/icme.2007.4285076",

language = "English",

isbn = "1424410177",

series = "Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007",

publisher = "IEEE Computer Society",

pages = "2018--2021",

booktitle = "Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007",

note = "IEEE International Conference onMultimedia and Expo, ICME 2007 ; Conference date: 02-07-2007 Through 05-07-2007",

}

Arsić, D, Schuller, B & Rigoll, G 2007, Suspicious behavior detection in public transport by fusion of low-level video descriptors. in Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007., 4285076, Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007, IEEE Computer Society, pp. 2018-2021, IEEE International Conference onMultimedia and Expo, ICME 2007, Beijing, China, 2/07/07. https://doi.org/10.1109/icme.2007.4285076

Suspicious behavior detection in public transport by fusion of low-level video descriptors. / Arsić, Dejan; Schuller, Björn ; Rigoll, Gerhard.
Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007. IEEE Computer Society, 2007. p. 2018-2021 4285076 (Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - Recently great interest has been shown in the visual surveillance of public transportation systems. The challenge is the automated analysis of passenger's behaviors with a set of visual low-level features, which can be extracted robustly. On a set of global motion features computed in different parts of the image, here the complete image, the face and skin color regions, a classification with Support Vector Machines is performed. Test-runs on a database of aggressive, cheerful, intoxicated, nervous, neutral and tired behavior in an airplane situation show promising results.

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T3 - Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007

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Arsić D, Schuller B , Rigoll G. Suspicious behavior detection in public transport by fusion of low-level video descriptors. In Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007. IEEE Computer Society. 2007. p. 2018-2021. 4285076. (Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007). doi: 10.1109/icme.2007.4285076

Suspicious behavior detection in public transport by fusion of low-level video descriptors

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Keywords

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