Face texture synthesis from multiple images via sparse and dense correspondence

Shugo Yamaguchi, Shigeo Morishima

    研究成果: Conference contribution

    2 引用 (Scopus)

    抜粋

    We have a desire to edit images for various purposes such as art, entertainment, and film production so texture synthesis methods have been proposed. Especially, PatchMatch algorithm [Barnes et al. 2009] enabled us to easily use many image editing tools. However, these tools are applied to one image. If we can automatically synthesize from various examples, we can create new and higher quality images. Visio-lization [Mohammed et al. 2009] generated average face by synthesis of face image database. However, the synthesis was applied block-wise so there were artifacts on the result and free form features of source images such as wrinkles could not be preserved. We proposed a new synthesis method for multiple images. We applied sparse and dense nearest neighbor search so that we can preserve both input and source database image features. Our method allows us to create a novel image from a number of examples.

    元の言語English
    ホスト出版物のタイトルSA 2016 - SIGGRAPH ASIA 2016 Technical Briefs
    出版者Association for Computing Machinery, Inc
    ISBN(電子版)9781450345415
    DOI
    出版物ステータスPublished - 2016 11 28
    イベント2016 SIGGRAPH ASIA Technical Briefs, SA 2016 - Macau, China
    継続期間: 2016 12 52016 12 8

    Other

    Other2016 SIGGRAPH ASIA Technical Briefs, SA 2016
    China
    Macau
    期間16/12/516/12/8

    ASJC Scopus subject areas

    • Computer Vision and Pattern Recognition
    • Computer Graphics and Computer-Aided Design

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  • これを引用

    Yamaguchi, S., & Morishima, S. (2016). Face texture synthesis from multiple images via sparse and dense correspondence. : SA 2016 - SIGGRAPH ASIA 2016 Technical Briefs [a14] Association for Computing Machinery, Inc. https://doi.org/10.1145/3005358.3005386