Motion Estimation And Segmentation

    Authors

    T. Y. Tian;M. Shah

    Comments

    Authors: contact us about adding a copy of your work at STARS@ucf.edu

    Abbreviated Journal Title

    Mach. Vis. Appl.

    Keywords

    optical flow; motion boundaries; line process; Markov random fields; mean field techniques; OPTICAL-FLOW; VISUAL-MOTION; FIELDS; PARALLEL; VISION; Computer Science, Artificial Intelligence; Computer Science, ; Cybernetics; Engineering, Electrical & Electronic

    Abstract

    In the general structure-from-motion (SFM) problem involving several moving objects in a scene, the essential first step is to segment moving objects independently. We attempt to deal with the problem of optical flow estimation and motion segmentation over a pair of images. We apply a mean field technique to determine optical flow and motion boundaries and present a deterministic algorithm. Since motion discontinuities represented by line process are embedded in the estimation of the optical flow, our algorithm provides accurate estimates of optical flow especially along motion boundaries and handles occlusion and multiple motions. We show that the proposed algorithm outperforms other well-known algorithms in terms of estimation accuracy and timing.

    Journal Title

    Machine Vision and Applications

    Volume

    9

    Issue/Number

    1

    Publication Date

    1-1-1996

    Document Type

    Article

    Language

    English

    First Page

    32

    Last Page

    42

    WOS Identifier

    WOS:A1996UX91500005

    ISSN

    0932-8092

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