Human-object maps for daily activity recognition

Haruya Ishikawa, Yuchi Ishikawa, Shuichi Akizuki, Yoshimitsu Aoki

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

    Abstract

    In the field of action recognition, when and where an interaction between a human and an object happens has the potential to be valid information in enhancing action recognition accuracy. Especially, in daily life where each activities are performed in longer time frame, conventional short term action recognition may fail to generalize do to the variety of shorter actions that could take place during the activity. In this paper, we propose a novel representation of human object interaction called Human-Object Maps (HOMs) for recognition of long term daily activities. HOMs are 2D probability maps that represents spatio-temporal information of human object interaction in a given scene. We analyzed the effectiveness of HOMs as well as features relating to the time of the day in daily activity recognition. Since there are no publicly available daily activity dataset that depicts daily routines needed for our task, we have created a new dataset that contains long term activities. Using this dataset, we confirm that our method enhances the prediction accuracy of the conventional 3D ResNeXt action recognition method from 86.31% to 97.89%.

    Original languageEnglish
    Title of host publicationProceedings of the 16th International Conference on Machine Vision Applications, MVA 2019
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    ISBN (Electronic)9784901122184
    DOIs
    Publication statusPublished - 2019 May
    Event16th International Conference on Machine Vision Applications, MVA 2019 - Tokyo, Japan
    Duration: 2019 May 272019 May 31

    Publication series

    NameProceedings of the 16th International Conference on Machine Vision Applications, MVA 2019

    Conference

    Conference16th International Conference on Machine Vision Applications, MVA 2019
    CountryJapan
    CityTokyo
    Period19/5/2719/5/31

    ASJC Scopus subject areas

    • Computer Science Applications
    • Signal Processing
    • Computer Vision and Pattern Recognition

    Cite this

    Ishikawa, H., Ishikawa, Y., Akizuki, S., & Aoki, Y. (2019). Human-object maps for daily activity recognition. In Proceedings of the 16th International Conference on Machine Vision Applications, MVA 2019 [8757896] (Proceedings of the 16th International Conference on Machine Vision Applications, MVA 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/MVA.2019.8757896