Conversational Group Detection Based on Social Context Using Graph Clustering Algorithm

Shoichi Inaba, Yoshimitsu Aoki

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    4 Citations (Scopus)

    Abstract

    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.

    Original languageEnglish
    Title of host publicationProceedings - 12th International Conference on Signal Image Technology and Internet-Based Systems, SITIS 2016
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages526-531
    Number of pages6
    ISBN (Electronic)9781509056989
    DOIs
    Publication statusPublished - 2017 Apr 21
    Event12th International Conference on Signal Image Technology and Internet-Based Systems, SITIS 2016 - Naples, Italy
    Duration: 2016 Nov 282016 Dec 1

    Other

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

    Keywords

    • Conversational group detection
    • F-formation
    • graph clustering

    ASJC Scopus subject areas

    • Computer Vision and Pattern Recognition
    • Radiology Nuclear Medicine and imaging
    • Computer Networks and Communications
    • Signal Processing

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  • Cite this

    Inaba, S., & Aoki, Y. (2017). Conversational Group Detection Based on Social Context Using Graph Clustering Algorithm. In Proceedings - 12th International Conference on Signal Image Technology and Internet-Based Systems, SITIS 2016 (pp. 526-531). [7907516] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SITIS.2016.89