The W-Penalty and its Application to Alpha Matting with Sparse Labels

Stephen Tierney, Junbin Gao, Yi Guo

    Research output: Book chapter/Published conference paperConference paperpeer-review

    Abstract

    Alpha matting is an ill-posed problem, as such the user must supply dense partial labels for an acceptable solution to be reached. Unfortunately this labelling can be time consuming. In this paper we introduce the w-penalty function, which when incorporated into existing matting techniques allows users to supply extremely sparse input. The formulated objective function encourages driving matte values to 0 and 1. The experiments demonstrate the proposed model outperforms the state-of-the-art KNN matting algorithm. MATLAB code for our proposed method is freely available in the MatteKit package1..
    Original languageEnglish
    Title of host publicationProceedings of the 2014 International Conference on Digital Image Computing: Techniques and Applications
    Place of PublicationUnited States
    PublisherIEEE, Institute of Electrical and Electronics Engineers
    Pages1-7
    Number of pages7
    ISBN (Electronic)9781479954094
    DOIs
    Publication statusPublished - 2014
    Event2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA) - Novotel Wollongong Northbeach Hotel, Wollongong, Australia
    Duration: 25 Nov 201427 Nov 2014
    https://ssl.informatics.uow.edu.au/dicta2014/

    Conference

    Conference2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA)
    Country/TerritoryAustralia
    CityWollongong
    Period25/11/1427/11/14
    OtherThe International Conference on Digital Image Computing: Techniques and Applications (DICTA) is an International Conference on computer vision, image processing, pattern recognition, and related areas. DICTA was established as a biennial conference in 1991 and became an annual event in 2007. It is the premier conference of the Australian Pattern Recognition Society (APRS).
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