TexasScholarWorks
    • Login
    • Submit
    View Item 
    •   Repository Home
    • UT Electronic Theses and Dissertations
    • UT Electronic Theses and Dissertations
    • View Item
    • Repository Home
    • UT Electronic Theses and Dissertations
    • UT Electronic Theses and Dissertations
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Temporal spatio-velocity transform and its applications

    Thumbnail
    View/Open
    satok55505.pdf (9.944Mb)
    Date
    2006
    Author
    Sato, Koichi
    Share
     Facebook
     Twitter
     LinkedIn
    Metadata
    Show full item record
    Abstract
    Object tracking is important in various applications such as video surveillance systems, video annotation systems, and human interaction classification systems. Occlusion and noise are the most significant problems in object tracking. In order to overcome these problems, I introduce the temporal spatio-velocity (TSV) transform, which extracts pixel velocities from image sequences. The TSV transform appends the velocity axes to the image sequences and separates occluding objects based on their velocities. The TSV transform is derived from the Hough transform over windowed spatio-temporal images. I present the methodology of the transform and its implementation in an iterative computational form. The intensity at each pixel in the TSV image represents a measure of the likelihood of occurrence of a pixel with instantaneous velocity in the current position. Binarization of the TSV image extracts blobs based on the similarity of velocity and position. The TSV transform provides an efficient way to remove noise by focusing on stable velocities, and constructs noise-free blobs. In this dissertation, I introduce three applications using the TSV transform. The applications are (i) human interaction recognition system, (ii) object tracking system in occluding environments, and (iii) soccer player tracking system. The human interaction recognition system uses side-view image sequences and tracks persons walking on sidewalks. Then it recognizes the interactions between two persons such as “two persons meet from different directions” and “one person follows another person”. The system correctly tracks persons and recognizes the interactions between them. The object tracking system in occluding environments tracks moving objects behind static obstacles, such as trees and fences. Although the static obstacles divide moving objects into several pieces both temporally and spatially, the system correctly tracks the objects. The soccer player tracking system tracks soccer players and referees using the ordinary TV broadcasting images. Although the soccer players make complex movements and the camera moves frequently, the system correctly tracks the players and referees.
    Department
    Electrical and Computer Engineering
    Description
    text
    URI
    http://hdl.handle.net/2152/2637
    Collections
    • UT Electronic Theses and Dissertations

    University of Texas at Austin Libraries
    • facebook
    • twitter
    • instagram
    • youtube
    • CONTACT US
    • MAPS & DIRECTIONS
    • JOB OPPORTUNITIES
    • UT Austin Home
    • Emergency Information
    • Site Policies
    • Web Accessibility Policy
    • Web Privacy Policy
    • Adobe Reader
    Subscribe to our NewsletterGive to the Libraries

    © The University of Texas at Austin

     

     

    Browse

    Entire RepositoryCommunities & CollectionsDate IssuedAuthorsTitlesSubjectsDepartmentsThis CollectionDate IssuedAuthorsTitlesSubjectsDepartments

    My Account

    Login

    Statistics

    View Usage Statistics

    Information

    About Contact Policies Getting Started Glossary Help FAQs

    University of Texas at Austin Libraries
    • facebook
    • twitter
    • instagram
    • youtube
    • CONTACT US
    • MAPS & DIRECTIONS
    • JOB OPPORTUNITIES
    • UT Austin Home
    • Emergency Information
    • Site Policies
    • Web Accessibility Policy
    • Web Privacy Policy
    • Adobe Reader
    Subscribe to our NewsletterGive to the Libraries

    © The University of Texas at Austin