Conversational Group Detection Based on Social Context Using Graph Clustering Algorithm

Shoichi Inaba, Yoshimitsu Aoki

    研究成果: Conference contribution

    5 被引用数 (Scopus)

    抄録

    With the development of single-person analysis in computer vision, social group analysis has received growing attention as the next area of research. In particular, group detection has been actively studied as the first step of social analysis. Here, group means an F-formation, that is, a spatial organization of people gathered for conversation. Popular group detection methods are based on coincidences in the visual attention field that are calculated from the position and body orientation of the individuals in the group. However, most previous studies have assumed that each member has the same visual attention field, and they do not consider changes in the scene over time. In this paper, we present a robust method for detection of time-varying F-formations in social space, its visual attention field model is based on the local environment. We present the results of an experiment that uses a dataset of multiple scenes, an analysis of these results validates the advantages of our method.

    本文言語English
    ホスト出版物のタイトルProceedings - 12th International Conference on Signal Image Technology and Internet-Based Systems, SITIS 2016
    出版社Institute of Electrical and Electronics Engineers Inc.
    ページ526-531
    ページ数6
    ISBN(電子版)9781509056989
    DOI
    出版ステータスPublished - 2017 4 21
    イベント12th International Conference on Signal Image Technology and Internet-Based Systems, SITIS 2016 - Naples, Italy
    継続期間: 2016 11 282016 12 1

    Other

    Other12th International Conference on Signal Image Technology and Internet-Based Systems, SITIS 2016
    国/地域Italy
    CityNaples
    Period16/11/2816/12/1

    ASJC Scopus subject areas

    • コンピュータ ビジョンおよびパターン認識
    • 放射線学、核医学およびイメージング
    • コンピュータ ネットワークおよび通信
    • 信号処理

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