Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications

Crowd monitoring based on Face Orientation Estimation

Authors
Xiaodong Wang, Hong Xiao, Rongxiao Guo, Jie Cui
Corresponding Author
Xiaodong Wang
Available Online November 2016.
DOI
https://doi.org/10.2991/aiea-16.2016.93How to use a DOI?
Keywords
Crowd Monitoring; Event; FOE; Overlap; Decay.
Abstract

Aim to the different needs, crowd monitoring and control is regarded to the key of modern surveillance. But, existing methods are still not good enough to be used on the large-scale spot, for the reasons of effect and efficiency. In fact, witnesses, who stay on the spot, practically act as "smart" sensors to the incidents. Thus, to detect their responds to events are effective to surveillance. Among all kinds of human actions, face orientation is easy to be detected; meanwhile it also implies plenty of immediacy with respect to the event. This paper presents a method of crowd monitoring based on face orientation estimation. According to preliminary experiment, it is proved valid and feasible.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications
Series
Advances in Computer Science Research
Publication Date
November 2016
ISBN
978-94-6252-270-1
ISSN
2352-538X
DOI
https://doi.org/10.2991/aiea-16.2016.93How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Xiaodong Wang
AU  - Hong Xiao
AU  - Rongxiao Guo
AU  - Jie Cui
PY  - 2016/11
DA  - 2016/11
TI  - Crowd monitoring based on Face Orientation Estimation
BT  - Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications
PB  - Atlantis Press
SP  - 521
EP  - 525
SN  - 2352-538X
UR  - https://doi.org/10.2991/aiea-16.2016.93
DO  - https://doi.org/10.2991/aiea-16.2016.93
ID  - Wang2016/11
ER  -