九州大学COI拠点情報科学部会で取り組んでいる、群衆映像から単に密な状態なのか、何らかのイベントで賑わっているのかを定量的に識別可能にする数値指標の策定と評価に関する論文が、IEEE ACCESSに採択されました。
福岡市実証実験フルサポート事業の元、本COIでは川端通り商店街にカメラを設置し、賑わいや密の計測を行っています。一見同じような群衆に見えても、単に商店街を素通りしている人々なのか、グループで観光に来ている集団なのか、など群衆の属性がわかりません。本研究成果は、同じような映像であっても、人の動きベクトルを考慮することで、群衆の属性を判別することを可能にするものです。
Mohamed A. Abdelwahab, Shizuo Kaji, Maiya Hori, Shigeru Takano, Yutaka Arakawa, Rin-ichiro Taniguchi
Measuring “Nigiwai” from Pedestrian Movement Journal Article
In: IEEE Access, vol. 9, pp. 24859 - 24871, 2021, ISSN: 2169-3536.
@article{9345686,
title = {Measuring “Nigiwai” from Pedestrian Movement},
author = {Mohamed A. Abdelwahab, Shizuo Kaji, Maiya Hori, Shigeru Takano, Yutaka Arakawa, Rin-ichiro Taniguchi},
url = {https://youtu.be/Jd_vKuU4HXI},
doi = {10.1109/ACCESS.2021.3056698},
issn = {2169-3536},
year = {2021},
date = {2021-02-05},
journal = {IEEE Access},
volume = {9},
pages = {24859 - 24871},
abstract = {The analysis of the movement of people in a shopping area with the aim of improving marketing is an important research topic. Many conventional methods are dependent on the density of people in the area, which is easily estimated by counting the people entering or exiting the area. However, a high density does not always mean an increase in activity, as certain people are simply passing the area at a given time. The primary goal of this study was to introduce a set of indicators for measuring the bustle of the area, which we call “Nigiwai,” from pedestrian movement by using an analogy from classical kinematics. Such indicators can be used to measure the impact of promotional events and to optimize the design of the area. Our novel indicators were evaluated with simulated pedestrian scenarios and were demonstrated to distinguish shopping scenarios from those in which people move around without shopping successfully, even when the latter scenarios had much higher densities. The indicators were computed solely from the pedestrian trajectory, which can easily be obtained from ordinary sensors using deep learning-based techniques. As a demonstration with real data, we applied our method to a video of a street and provided a visualization of the indicators.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The analysis of the movement of people in a shopping area with the aim of improving marketing is an important research topic. Many conventional methods are dependent on the density of people in the area, which is easily estimated by counting the people entering or exiting the area. However, a high density does not always mean an increase in activity, as certain people are simply passing the area at a given time. The primary goal of this study was to introduce a set of indicators for measuring the bustle of the area, which we call “Nigiwai,” from pedestrian movement by using an analogy from classical kinematics. Such indicators can be used to measure the impact of promotional events and to optimize the design of the area. Our novel indicators were evaluated with simulated pedestrian scenarios and were demonstrated to distinguish shopping scenarios from those in which people move around without shopping successfully, even when the latter scenarios had much higher densities. The indicators were computed solely from the pedestrian trajectory, which can easily be obtained from ordinary sensors using deep learning-based techniques. As a demonstration with real data, we applied our method to a video of a street and provided a visualization of the indicators.