Face texture synthesis from multiple images via sparse and dense correspondence

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

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.

本文言語English
ホスト出版物のタイトルSA 2016 - SIGGRAPH ASIA 2016 Technical Briefs
出版社Association for Computing Machinery, Inc
ISBN(電子版)9781450345415
DOI
出版ステータス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

出版物シリーズ

名前SA 2016 - SIGGRAPH ASIA 2016 Technical Briefs

Other

Other2016 SIGGRAPH ASIA Technical Briefs, SA 2016
国/地域China
CityMacau
Period16/12/516/12/8

ASJC Scopus subject areas

  • コンピュータ ビジョンおよびパターン認識
  • コンピュータ グラフィックスおよびコンピュータ支援設計

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