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Authors: Shigeru Takano ; Maiya Hori ; Takayuki Goto ; Seiichi Uchida ; Ryo Kurazume and Rin-ichiro Taniguchi

Affiliation: Kyushu University, Japan

Keyword(s): People Tracking, Anomaly Detection, Prediction of People Flow, Deep Learning.

Related Ontology Subjects/Areas/Topics: Applications ; Computer Vision, Visualization and Computer Graphics ; Human-Computer Interaction ; Methodologies and Methods ; Motion and Tracking ; Motion, Tracking and Stereo Vision ; Pattern Recognition ; Physiological Computing Systems

Abstract: This paper proposes prediction methods for people flows and anomalies in people flows on a university campus. The proposed methods are based on deep learning frameworks. By predicting the statistics of people flow conditions on a university campus, it becomes possible to create applications that predict future crowded places and the time when congestion will disappear. Our prediction methods will be useful for developing applications for solving problems in cities.

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Paper citation in several formats:
Takano, S.; Hori, M.; Goto, T.; Uchida, S.; Kurazume, R. and Taniguchi, R. (2017). Deep Learning-based Prediction Method for People Flows and Their Anomalies. In Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-222-6; ISSN 2184-4313, SciTePress, pages 676-683. DOI: 10.5220/0006248806760683

@conference{icpram17,
author={Shigeru Takano. and Maiya Hori. and Takayuki Goto. and Seiichi Uchida. and Ryo Kurazume. and Rin{-}ichiro Taniguchi.},
title={Deep Learning-based Prediction Method for People Flows and Their Anomalies},
booktitle={Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2017},
pages={676-683},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006248806760683},
isbn={978-989-758-222-6},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Deep Learning-based Prediction Method for People Flows and Their Anomalies
SN - 978-989-758-222-6
IS - 2184-4313
AU - Takano, S.
AU - Hori, M.
AU - Goto, T.
AU - Uchida, S.
AU - Kurazume, R.
AU - Taniguchi, R.
PY - 2017
SP - 676
EP - 683
DO - 10.5220/0006248806760683
PB - SciTePress

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