Shared more. Cited more. Safe forever.
    • advanced search
    • submit works
    • about
    • help
    • contact us
    • login
    View Item 
    •   MOspace Home
    • University of Missouri-Columbia
    • Graduate School - MU Theses and Dissertations (MU)
    • Theses and Dissertations (MU)
    • Dissertations (MU)
    • 2010 Dissertations (MU)
    • 2010 MU dissertations - Freely available online
    • View Item
    •   MOspace Home
    • University of Missouri-Columbia
    • Graduate School - MU Theses and Dissertations (MU)
    • Theses and Dissertations (MU)
    • Dissertations (MU)
    • 2010 Dissertations (MU)
    • 2010 MU dissertations - Freely available online
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.
    advanced searchsubmit worksabouthelpcontact us

    Browse

    All of MOspaceCommunities & CollectionsDate IssuedAuthor/ContributorTitleIdentifierThesis DepartmentThesis AdvisorThesis SemesterThis CollectionDate IssuedAuthor/ContributorTitleIdentifierThesis DepartmentThesis AdvisorThesis Semester

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular AuthorsStatistics by Referrer

    Linguistic summarization of human activity

    Anderson, Derek T., 1979-
    View/Open
    [PDF] public.pdf (2.029Kb)
    [PDF] short.pdf (70.41Kb)
    [PDF] research.pdf (6.108Mb)
    Date
    2010
    Format
    Thesis
    Metadata
    [+] Show full item record
    Abstract
    The thesis advanced herein is that linguistic summarization is essential for the reliable succinct modeling and inference of human activity. It is also asserted that the inherent and unavoidable uncertainty is linguistic and fuzzy. Advantages of the proposed work include the generation of human interpretable confidence values, improved rejection of unknown activity, information reduction, complexity management, and the recognition of adverse events. Specifically, a computer vision-based hierarchical soft-computing linguistic summarization framework is proposed. First, images are summarized through the identification of a human and a three-dimensional object called voxel person is constructed. Next, approximate reasoning is used to linguistically summarize the state of the human at each moment, i.e. image, using features extracted from voxel person. Subsequently, temporal linguistic summarizations are produced from the state membership time series. State summaries are used to infer activity, which are also linguistically summarized and subsequently used in a hierarchical similar fashion to recognize additional specific types of higher level activity. A system comprised of two levels is described for the goal of elderly activity recognition. The system parameters are designed under the supervision of nurses. The results are compared to probabilistic graphical models for three data sets consisting of student and nurse trained and supervised stunt actor activities.
    URI
    https://hdl.handle.net/10355/8878
    https://doi.org/10.32469/10355/8878
    Degree
    Ph. D.
    Thesis Department
    Electrical and computer engineering (MU)
    Rights
    OpenAccess.
    This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License.
    Collections
    • Electrical Engineering and Computer Science electronic theses and dissertations (MU)
    • 2010 MU dissertations - Freely available online

    Send Feedback
    hosted by University of Missouri Library Systems
     

     


    Send Feedback
    hosted by University of Missouri Library Systems