• Login
    View Item 
    •   Home
    • Research
    • Conference Papers
    • View Item
    •   Home
    • Research
    • Conference Papers
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of KAUSTCommunitiesIssue DateSubmit DateThis CollectionIssue DateSubmit Date

    My Account

    Login

    Quick Links

    Open Access PolicyORCID LibguideTheses and Dissertations LibguideSubmit an Item

    Statistics

    Display statistics

    Shape-tailored local descriptors and their application to segmentation and tracking

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Thumbnail
    Name:
    Khan_Shape-Tailored_Local_Descriptors_2015_CVPR_paper.pdf
    Size:
    7.234Mb
    Format:
    PDF
    Description:
    Accepted Manuscript
    Download
    Type
    Conference Paper
    Authors
    Khan, Naeemullah cc
    Algarni, Marei Saeed Mohammed cc
    Yezzi, Anthony
    Sundaramoorthi, Ganesh cc
    KAUST Department
    Computer Science Program
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Electrical Engineering Program
    Visual Computing Center (VCC)
    Date
    2015-10-15
    Online Publication Date
    2015-10-15
    Print Publication Date
    2015-06
    Permanent link to this record
    http://hdl.handle.net/10754/580029
    
    Metadata
    Show full item record
    Abstract
    We propose new dense descriptors for texture segmentation. Given a region of arbitrary shape in an image, these descriptors are formed from shape-dependent scale spaces of oriented gradients. These scale spaces are defined by Poisson-like partial differential equations. A key property of our new descriptors is that they do not aggregate image data across the boundary of the region, in contrast to existing descriptors based on aggregation of oriented gradients. As an example, we show how the descriptor can be incorporated in a Mumford-Shah energy for texture segmentation. We test our method on several challenging datasets for texture segmentation and textured object tracking. Experiments indicate that our descriptors lead to more accurate segmentation than non-shape dependent descriptors and the state-of-the-art in texture segmentation.
    Citation
    Khan, Naeemullah, Marei Algarni, Anthony Yezzi, and Ganesh Sundaramoorthi. "Shape-Tailored Local Descriptors and their Application to Segmentation and Tracking." In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3890-3899. 2015
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
    Conference/Event name
    IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015
    DOI
    10.1109/CVPR.2015.7299014
    Additional Links
    http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7299014
    ae974a485f413a2113503eed53cd6c53
    10.1109/CVPR.2015.7299014
    Scopus Count
    Collections
    Conference Papers; Computer Science Program; Electrical and Computer Engineering Program; Visual Computing Center (VCC); Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

    entitlement

     
    DSpace software copyright © 2002-2022  DuraSpace
    Quick Guide | Contact Us | KAUST University Library
    Open Repository is a service hosted by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items. For anonymous users the allowed maximum amount is 50 search results.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.