Dominant Codewords Selection with Topic Model for Action Recognition

Hirokatsu Kataoka, Kenji Iwata, Yutaka Satoh, Masaki Hayashi, Yoshimitsu Aoki, Slobodan Ilic

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

    Abstract

    In this paper, we propose a framework for recognizing human activities that uses only in-topic dominant codewords and a mixture of intertopic vectors. Latent Dirichlet allocation (LDA) is used to develop approximations of human motion primitives, these are mid-level representations, and they adaptively integrate dominant vectors when classifying human activities. In LDA topic modeling, action videos (documents) are represented by a bag-of-words (input from a dictionary), and these are based on improved dense trajectories ([18]). The output topics correspond to human motion primitives, such as finger moving or subtle leg motion. We eliminate the impurities, such as missed tracking or changing light conditions, in each motion primitive. The assembled vector of motion primitives is an improved representation of the action. We demonstrate our method on four different datasets.

    Original languageEnglish
    Title of host publicationProceedings - 29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016
    PublisherIEEE Computer Society
    Pages770-777
    Number of pages8
    ISBN (Electronic)9781467388504
    DOIs
    Publication statusPublished - 2016 Dec 16
    Event29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016 - Las Vegas, United States
    Duration: 2016 Jun 262016 Jul 1

    Other

    Other29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016
    CountryUnited States
    CityLas Vegas
    Period16/6/2616/7/1

    ASJC Scopus subject areas

    • Computer Vision and Pattern Recognition
    • Electrical and Electronic Engineering

    Fingerprint Dive into the research topics of 'Dominant Codewords Selection with Topic Model for Action Recognition'. Together they form a unique fingerprint.

  • Cite this

    Kataoka, H., Iwata, K., Satoh, Y., Hayashi, M., Aoki, Y., & Ilic, S. (2016). Dominant Codewords Selection with Topic Model for Action Recognition. In Proceedings - 29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016 (pp. 770-777). [7789591] IEEE Computer Society. https://doi.org/10.1109/CVPRW.2016.101