| Project/Area Number |
17K00256
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Perceptual information processing
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| Research Institution | Kindai University |
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Principal Investigator |
Habe Hitoshi 近畿大学, 理工学部, 准教授 (80346072)
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| Project Period (FY) |
2017-04-01 – 2020-03-31
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| Project Status |
Completed (Fiscal Year 2019)
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| Budget Amount *help |
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2019: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2018: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2017: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Keywords | 群衆行動 / 不審行動 / 人物検出 / 畳み込みニューラルネットワーク / 低解像度映像 / 群衆映像 / 意図 / 状態 / 映像解析 |
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| Outline of Final Research Achievements |
In this study, we developed and verified an image processing technique focusing on the change in facial orientation and mainly applying it to the detection of suspicious persons. For face detection and face change estimation, we used TinyFace and Deepgaze, both of which are considered to have the highest level of accuracy in their respective fields, to estimate the intentions of the person, especially the person acting suspiciously, using the time series of face orientation data obtained from TinyFace and Deepgaze. From the time series data, we chose to identify people who moved strangely or unnaturally large in comparison with other people, and identified them as people who were acting suspiciously. In order to verify the effectiveness of this method, we conducted experiments with a video dataset assuming spectator seats in a stadium.
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| Academic Significance and Societal Importance of the Research Achievements |
顔検出および顔向き変化の推定といった「低レベル」な情報の推定は深層学習によって大いに発展してきている．それに比べて，意図や状態といった「高レベル」な情報の推定は大きな課題となっていて様々なグループが研究を行っている．本研究も，そのような課題にチャレンジしたものであり，学術的な意義が大きい．また，不審人物候補の検出はセキュリティ，防犯などの社会的な要求が大きい応用分野であるので，本研究の社会的な意義も大きいと言える．
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