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Hierarchical Person Identification using Individual and Group Features

Research Project

Project/Area Number 18K11361
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Review Section Basic Section 61010:Perceptual information processing-related
Research InstitutionTsuda University

Principal Investigator

Sugimura Daisuke  津田塾大学, 学芸学部, 准教授 (10712052)

Co-Investigator(Kenkyū-buntansha) 浜本 隆之  東京理科大学, 工学部電気工学科, 教授 (10297624)
Project Period (FY) 2018-04-01 – 2022-03-31
Project Status Completed (Fiscal Year 2021)
Budget Amount *help
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2020: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2019: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2018: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Keywords知覚情報処理 / 画像認識 / 個人認証 / 人物照合 / 知覚情報処理関連
Outline of Final Research Achievements

We develop a method for person identification from surveillance videos. Conventional methods used color and shape features of individual person. However, the information that can be extracted from individual tends to be limited; thus, there is a certain limit to the improvement of identification performance. In addition, when the number of people to be identified increases, the identification performance generally deteriorates. In this research, we investigate a hierarchical identification approach for groups and individuals. If we can analyze the information of a group, we can use the features related to the group. Furthermore, if the group can be identified, the number of candidates to be identified can be decreased because it can be considered that groups contain only a few people. Based on this hierarchical identification approach, we develop techniques of a person re-identification and person identification.

Academic Significance and Societal Importance of the Research Achievements

映像からの人物照合技術の高度化は,安心・安全な社会環境の実現において必要不可欠である.人物個人だけでなく集団の情報を照合に活用する観点は,これまでの従来技術にないものである.また,集団・個人の階層的認識は,照合対象の増大に伴う性能低下という当該分野の本質的な課題の解決を試みる独創的なアプローチである.このように,本研究課題で検討および開発した技術は,当該分野にインパクトを与えるものであると考える.

Report

(5 results)
  • 2021 Annual Research Report   Final Research Report ( PDF )
  • 2020 Research-status Report
  • 2019 Research-status Report
  • 2018 Research-status Report
  • Research Products

    (5 results)

All 2022 2021 2020 2019

All Journal Article (1 results) Presentation (4 results)

  • [Journal Article] 多段階識別に基づく瞬き動作認証手法の検討2020

    • Author(s)
      杉村大輔,中野真理子,徳永律子,内田葉子
    • Journal Title

      日本工業出版(株) ,画像ラボ

      Volume: 31 Pages: 32-36

    • Related Report
      2019 Research-status Report
  • [Presentation] 顔特徴と発話時の唇の動きに基づく階層的生体認証2022

    • Author(s)
      安永綾花,岡田祐花,園櫻子,杉村大輔
    • Organizer
      電子情報通信学会総合大会
    • Related Report
      2021 Annual Research Report
  • [Presentation] 人物移動軌跡推定のためのグラフニューラルネットワークに基づくリンク予測2021

    • Author(s)
      渡邉丈裕,前田慶博,杉村大輔,浜本隆之
    • Organizer
      映像メディア処理シンポジウム
    • Related Report
      2021 Annual Research Report
  • [Presentation] 遠距離・近距離における多段階瞬き動作認証2019

    • Author(s)
      中野真理子,徳永律子,内田葉子,杉村大輔
    • Organizer
      電子情報通信学会画像工学研究会
    • Related Report
      2019 Research-status Report
  • [Presentation] 集団・個人の見え特徴の併用によるカメラ間人物照合2019

    • Author(s)
      稲見慎吾,杉村大輔,浜本隆之
    • Organizer
      電子情報通信学会画像工学研究会
    • Related Report
      2018 Research-status Report

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Published: 2018-04-23   Modified: 2023-07-20  

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